Spam classification/MICROSOFT – T 0022/ 12 – 16 November 2015

This decision was particularly concerned with whether a technical effect exists with a certain classification of emails.

Object of the Invention:

  • the invention concerns the classification of emails, e.g. as either spam or legitimate mail
  • an incoming email is first analysed to determine whether it contains one or more features in a set of predetermined features that are particularly characteristic of spam
  • two types of feature are used: word-oriented and “handcrafted
  • the former refers to the presence of particular words, or stems of words, the latter to features determined through human judgement alone
  • examples of a handcrafted feature is a sender address, since most spam messages are sent at night from “.com” or “.net” domains

Board I (inventive step):

  • the Board agrees with the Examining Division that the classification of messages as a function of their content is not technical per se
  • it is immaterial whether the messages are electronic messages, because, even though an email has technical properties, it is the content of the email that is classified
  • mathematical methods as such are not technical and the application of a mathematical method as such in a non-technical analysis of message content does not change that
  • if there is a technical effect, it can only reside in the automation of the email classification using a computer
  • the technicality of the computer is not enough to establish a technical effect of any method that it executes

Appellant I (inventive step):

  • a classification based on a combination of “handcrafted features” and “word oriented features” had the technical effect of reducing processing load

Board II (inventive step):

  • the Board is not persuaded that the alleged effect is actually achieved by the invention
  • there is no link between the word-oriented and handcrafted features, so that the latter reduces the processing involved in the former
  • the handcrafted features are, rather, a different class of features that the user considers indicative of spam, but which cannot be expressed in terms of the presence of individual words
  • simply adding a second class of features to the analysis increases the load rather than reducing it
  • furthermore, the Board does not consider that the de-automation of a computer-implemented method, by making a human perform steps that a computer could do automatically, is a technical solution to a technical problem
  • any reduction in computer processing would be a mere consequence of the de-automation
  • handcrafted features relate to information content that is considered as indicative of spam
  • including such features in the analysis might, if well chosen, improve the quality of the classification, but the designation of a second class of features does not provide a technical effect

Appellant II (inventive step):

  • the appellant argued, however, that there was a technical effect in the particular combination of an SVM and a sigmoid function
  • performing the method in two stages, first using an SVM, and then applying an adjustable sigmoid function as a threshold to the output of the SVM, reduced the processing load, which reduced the complexity of the computer implementation
  • thus, the invention was motivated by technical considerations of the computer implementation

Board III (inventive step):

  • the Board is not persuaded by the appellant’s arguments on this point
  • the Board does not find support, anywhere in the application, for the classifier being updated by adjusting the sigmoid parameters alone, without retraining the SVM
  • the generation of parameters for the classifier during the training phase involves two steps:
    • first the weight vector w is determined by conventional SVM training methods
    • second the optimal sigmoid parameters are calculated by using a maximum likelihood on the training data
  • there is nothing to suggest that re-training may involve only one of those steps, or that the classifier may be updated by simply adjusting the parameters A and B
  • on the contrary, it is the teaching of the application that, when the conditions of what is considered as spam change (e.g. when the user reclassifies a message) the whole classifier is retrained
  • furthermore, the Board does not consider that reducing the complexity of an algorithm is necessarily a technical effect, or evidence of underlying technical considerations
  • that is because complexity is an inherent property of the algorithm as such
  • if the design of the algorithm were motivated by a problem related to the internal workings of the computer, e.g. if it were adapted to a particular computer architecture, it could, arguably, be considered as technical (T 1358/09 referring to T 258/03)
  • however, the Board does not see any such motivations in the present case
  • thus, the Board is not persuaded that the use of an SVM in combination with a sigmoid threshold function contributes, technically, to the the computer implementation
  • the Board rather considers this to be a mathematical method
  • the technical implementation of the method consists in programming the computer to perform the method steps
  • this would have been a routine task for the skilled programmer
  • –> no inventive step

Classification method/COMPTEL – T 1784/06 – 21 September 2012

In this decision, the appellant criticises the COMVIK approach on several points. The Board disagrees. With regard to inventive step, according to the Board, there is a lack of “technical purpose” according to T1227/05.

Information from the author: “technical purpose” is no longer sufficient according to decision G1/19 for non-technical features to make a technical contribution. According to current case law (as of August 2024), in such a case a further or intended or implied technical use is required.

Object of the Invention:

  • data records, e. g. the duration and data volume of a telecommunication connection, that are sorted into service classes, in particular for rating and billing purposes
  • identifying the class of a service from a data record forms a performance bottleneck once the number of services is increased to the thousands
  • the application seeks to provide a method which can handle large numbers of service classes more efficiently than the conventional use of conditional statements does
  • the solution is based on reducing, as a first step, a large number of service classes into specific sets
  • these sets are then intersected in a final step
  • this algorithm classifies data records more efficiently

Board (COMVIK approach):

  • it would appear paradoxical to the Board to recognise an inventive step on the basis of a non-technical innovation (such as an organisational, administrative, commercial or mathematical algorithm) having no technical implication other than the (obvious) desire for its implementation on a general-purpose computer

Appellant I (COMVIK approach):

  • claimed subject-matter as a whole should be examined for the presence of an inventive step once the subject-matter as a whole has been found to meet the technology criterion of Article 52(1)(2)(3) EPC
  • Article 56 EPC 1973 should be applied independently of Article 52(1)(2)(3) EPC because Article 52(2) EPC has to be applied independently of Article 56 EPC 1973

Board I (COMVIK approach):

  • the Board does not accept such formal reasoning and points out that it is normal and often necessary for legal provisions to be in an asymmetric relationship or hierarchical dependency
  • for example, the novelty of a claim has to be examined independently of inventive step considerations, whereas a finding of inventiveness presupposes a novelty examination
  • another example is the validity of a priority claim which has to be checked independently of novelty and inventive step requirements, whereas novelty and inventive step cannot be established independently of the validity of a priority right.

Appellant II (COMVIK approach):

  • regarding the Board’s insistence on a technical problem when applying the problem-and-solution approach, the appellant disputes that such a requirement can be deduced from the EPC or introduced from its Implementing Regulations
  • the appellant refers inter alia to decision T 473/08 (by a different Board) to point out that “a non-technical problem can have a technical solution

Board II (COMVIK approach):

  • there is no divergence, the Board agrees to the statement that a non-technical problem can have a technical solution
  • on the other hand, where an intrinsically non-technical solution (mathematical algorithm) seeks to derive a technical character from the problem solved, the problem must be technical
  • this is the point on which the present case hinges

Appellant III (COMVIK approach):

  • another argument of the appellant refers to the legislative history of the EPC (travaux préparatoires) which is said not to provide any explicit support for a cumulative application of Article 52(2) EPC and Article 56 EPC 1973

Board III (COMVIK approach):

  • the restriction of substantive patent law to technical subject-matter is so self-evident that the founding fathers of the EPC did not even mention that requirement in the original (1973) version of Article 52(1)
  • the explicit clause “in all fields of technology” was not added to Article 52(1) until the Diplomatic Conference in the year 2000 harmonised the Article with the TRIPs treaty
  • nevertheless, Article 52(1) EPC has always been understood as referring to technical inventions

Board IV (inventive step):

  • as the algorithm is a mathematical (inter alia Boolean) method and mathematical methods as such are deemed to be non-inventions (Article 52(2)(3) EPC), a technical character of the algorithm could be recognised only if it served a technical purpose (T1227/05)
  • however, the automatic classification of data records according to claim 1 serves only the purpose of classifying the data records, without implying any technical use of the classification
  • the claim covers any non-technical (e.g. administrative or commercial) use of the classified data records
  • in the light of the description, the classification method prepares rating and billing procedures
  • the Board does not consider the result of the algorithm — a set of classified data records — as technical

Board V (inventive step):

  • enhanced speed of an algorithm, as compared to other algorithms, is not sufficient to establish a technical character of the algorithm (T 1227/05)
  • if a computer-implemented algorithm runs more quickly, the resulting saving in energy is a technical effect inherent to the normal interaction of software and hardware, i.e. it is not a “further” technical effect of the algorithmic program controlling the computer (T 1173/97)
  • the claimed algorithm may allow a data record to be processed in a parallel computer architecture as the various fields of a data record can be judged separately in a first level of processing
  • however, claim 1 is not limited to an implementation on a parallel hardware structure
  • in fact, the application as a whole is silent on parallel data processing (Parallel processing has been mentioned by the decision under appeal and addressed by the statement setting out the grounds of appeal)
  • –> no inventive step

Edge Detection – T 0165/ 12 – 6 July 2017

In this decision, the Board found that the description of the main request did not support the claim, as the description disclosed only one specific example of a merely general feature (“first phase congruency component”). In an auxiliary request, the appellant overcame this rejection, but the claimed subject-matter is still considered not to be inventive

Object of the Invention:

  • method for edge detection of an image
  • the method categorises pixels in the image as edge pixels or non-edge pixels

Board I (support by the description – main request):

  • in the application itself, no different way to determine the phase congruency at a pixel is disclosed than to calculate the ratio between the local energy at the pixel and the sum of Fourier components
  • also in the statement of grounds the appellant provided no additional example and, thus, failed to support its view that a different phase congruency component could be used
  • hence, it is a mere allegation that other “first phase congruency components” could be used
  • according to the established jurisprudence of the boards of appeal, the requirement of 84 EPC means that the subject-matter of the claim must be taken from the description and it is not admissible to claim something that is not described
  • in decision T 94/05, in particular, the board pointed out that the requirement for the claims to be supported by the description was intended to ensure that the extent of protection as defined by the patent claims corresponds to the technical contribution of the disclosed invention to the art
  • therefore the claims must reflect the actual contribution to the art in such a way that the skilled person is able to perform the invention in the entire range claimed
  • the skilled person, at least after reading the patent specification, taking account of his common general knowledge, and possibly also after carrying out normal experiments, must actually be provided with at least a plurality of different embodiment variants
  • in the present case, the use of the term “first phase congruence component” leaves it open, what other embodiments besides the “local energy” are envisaged
  • –> there is not enough support in the description for using the broad term “first phase congruency component” in the independent claims instead of the only embodiment disclosed in the specification, i.e. the “local energy”

Board II (inventive step – auxiliary request):

  • technical effect disclosed in the application is: “This allows for pixels that fail the phase congruency test, to be counted as edge pixels if their local energy satisfies the phase congruency component criteria.
  • a person skilled in the art recognizing that a first method for edge detection does not result in an expected number of edge pixels evidently has three straightforward possibilities to increase the number of edge pixels:
    1. by using another – better – method for edge detection
    2. by adapting the first method for edge detection (for instance by reducing a respective threshold that distinguishes between non-edge pixels and edge pixels)
    3. by using a further known method for edge detection, which provides different results (i.e. additional edge pixels) than the first method and combining the results of both methods
  • for instance, an example for an algorithm using different methods for detecting different kind of edges is disclosed in D3
  • choosing one out of these straightforward possibilities does not involve an inventive step
  • the Board does not see an inventive step in using the local energy method for finding additional edge pixels that were missed by the first method (as claimed) as compared to rejecting edge pixels by using the local energy method that were found by the first method, but should not be considered as edge pixels (as disclosed in D1)
  • this is considered a mere implementation detail, depending on the choice of criteria of the first method, which might cause too many or not enough edge pixels

Classification/BDGB ENTERPRISE SOFTWARE – T 1358/09 – 21 November 2014

This decision concerns the patentability of the classification of text documents. In this context, the Board clarifies whether the determination of claim features contributing to the technical character is made without reference to the prior art.

Object of the Invention:

  • the invention is concerned with the computerized classification of text documents
  • this is done by first building aclassification model” and then classifying documents using this classification model

Board I (sufficiency of disclosure):

  • the application does not explain several techniques in detail, and claim 1 does not specify any measure being taken to ensure linear separability
  • it may therefore be questioned whether the application is sufficiently disclosed over the whole scope claimed
  • however, the Board considers that this issue does not prevent it from examining for the presence of an inventive step
  • given the outcome of this examination the question of sufficiency of disclosure need not be answered

Board II (inventive step):

  • claim 1 defines a method for classifying text documents essentially in terms of an abstract mathematical algorithm
  • a mathematical algorithm contributes to the technical character of a computer-implemented method only in so far as it serves a technical purpose (T 1784/06)
  • in the present case, the algorithm serves the general purpose of classifying text documents
  • classification of text documents is certainly useful, as it may help to locate text documents with a relevant cognitive content, but does not qualify as a technical purpose
  • whether two text documents in respect of their textual content belong to the same “class” of documents is not a technical issue
  • the same position was taken in T 1316/09 which held that methods of text classification per se did not produce a relevant technical effect or provide a technical solution to any technical problem

Appellant I (inventive step):

  • the claimed invention could not be seen as the straightforward implementation of something which had been done manually before
  • when manually classifying a text document, a human being would read it through and assign a particular class to it on the basis of his understanding of the document
  • as was known from the domain of cognitive psychology, he would not consider all of the words in the document; words near its beginning would often already provide a clear indication of its semantic topic
  • the claimed automatic classification method on the other hand involved precise computation steps which no human being would ever perform when classifying documents
  • the claimed computerised method was highly efficient, in particular in comparison to classification methods disclosed in documents cited in the international search report

Board III (inventive step):

  • the Board agrees that a human being would not apply the claimed classification method to perform the task of classifying text documents
  • the Board accepts that the proposed computerised method may be faster than classification methods known from the prior art
  • however, the determination of the claim features which contribute to the technical character of the invention is made, at least in principle, without reference to the prior art (T 154/04)
  • it follows that a comparison with what a human being would do or with what is known from the prior art is not a suitable basis for distinguishing between technical and non-technical steps (T 1954/08)

Board IV (inventive step):

  • nevertheless, not all efficiency aspects of an algorithm are by definition without relevance for the question of whether the algorithm provides a technical contribution
  • if an algorithm is particularly suitable for being performed on a computer in that its design was motivated by technical considerations of the internal functioning of the computer, it may arguably be considered to provide a technical contribution to the invention (T 258/03)
  • however, such technical considerations must go beyond merely finding a computer algorithm to carry out some procedure (G 3/08)
  • in the present case no such technical considerations are present
  • the algorithm underlying the method of claim 1 does not go beyond a particular mathematical formulation of the task of classifying documents
  • the aim of this formulation is clearly to enable a computer to carry out this task, but no further consideration of the internal functioning of a computer can be recognised

Appellant II (inventive step):

  • the claimed method provided more reliable and objective results than manual classification, since it was independent of the human subjective understanding of the content of the documents

Board V (inventive step):

  • the Board does not contest that the claimed classification method may provide reliable and objective results, but this is an inherent property of deterministic algorithms
  • the mere fact that an algorithm leads to reproducible results does not imply that it makes a technical contribution
  • since the mathematical algorithm does not contribute to the technical character of the claimed method, an inventive step can be present only in its technical implementation
  • the technical implementation of the mathematical algorithm being obvious
  • –> no inventive step

Information from the author: “technical purpose” is no longer sufficient according to decision G1/19 for non-technical features to make a technical contribution. According to current case law (as of August 2024), in such a case a further or intended or implied technical use is required.

Categorization of Messages – T 1316/09 – 18 December 2012

In this decision, the Board does not see any technical effect with respect to the distinguishing features of the claimed subject-matter over the prior art.

Object of the Invention:

  • method and a system for suggesting automated responses to an incoming electronic message based on content analysis and categorisation

Board I (inventive step):

  • a decisive factor in any assessment of inventive step is the objective technical problem underlying the invention
  • the inventive solution of the objective technical problem must be based on the technical features of the invention as claimed
  • text classification per se, however, does not serve any technical purpose
  • neither does the combination of different methods of text categorisation per se provide any relevant technical effect that could form a valid basis for defining the objective technical problem
  • in the light of document D2, the invention seems merely to consist of proposing an alternative to the classifier 34 in the form of a “classifier committee” combining the rule-based scheme of D1 with an example-based classifier based on the k-nn algorithm disclosed in D1

Appellant (inventive step):

  • the distinguishing features of claim 1 over D2 lead to the following technical effects:
    • more relevant responses to an incoming message can be located, i.e. a greater number of irrelevant responses are filtered out
    • the time and effort required to respond to incoming messages is reduced
    • messages can be processed at a greater rate, i.e. more efficiently
    • the quality of responses to messages can be improved
    • the synergistic combination of query based classification and example based classification yields greater efficiency and better results than either method taken alone
  • the skilled person is confronted with the objective technical problem of how to more efficiently and effectively provide a response to an incoming message

Board II (inventive step):

  • the alleged effects are speculative, considering that nothing in the claimed invention prevents the intersection of the categories provided by a query and by the example-based algorithm being empty and hence that the claimed method is a complete failure
  • even more importantly, the appellant did not provide any substantive reason why a more efficient and better categorisation of the informational content of an incoming electronic message qualifies as a technical effect at all and why such an advancement over the prior art has technical character
  • no inventive step

Text mining/BOEING – T 1416/06 – 24 April 2009

In this decision the board considers the data does not form a physical entity.

Object of the Invention:

  • the subject matter is directed to a method of representing a document collection
  • the method is to a large extent defined in terms of equations
  • the purpose of the method is to present the information in a way that can be more easily understood or evaluated by a user

Board I (field of technology):

  • at the bottom of the method is a mathematical technique known as orthogonal decomposition
  • this technique is generally applied to large matrices and, like many mathematical functions, can be represented graphically
  • it is typical for mathematical representations that they involve pure numbers, ie abstract data, having no physical connotation
  • in the present invention the representations are of documents and the terms used in the documents
  • thus, although the data have a certain “meaning“, they remain abstract
  • they can hardly be regarded as forming a physical entity, nor does the method result in a change in the data but merely in their representation (T 208/84)
  • it could therefore be argued that the invention – apart from its implementation – is essentially a mathematical method pursuant to Article 52(2)(a) EPC, resulting in a presentation of information pursuant to Article 52(2)(d) EPC

Image classification / STMICROELECTRONICS – T 1148/05 – 27 May 2009

In this decision, a method of image classification was claimed. The Board assumed that all features contribute to the technical character and that the sufficiency of disclosure was given.

Object of the Invention:

  • image classification method for classifying digital images into photographs, texts, and graphics
  • conventional heuristic methods implemented by expert systems present a number of drawbacks, in particular the computational complexity required for analysing the large number of pixels of an image
  • another problem is touched on by the “impossibility of optimising analysis using parallel architectures”
  • the thrust of the application is for constructing a classification algorithm (“tree-structured classifier”) which is both powerful in terms of class discrimination and efficient in terms of processing speed

Board I (sufficiency of disclosure (Article 83 EPC):

  • examining division has argued that the application does not disclose any specific example of a tree classifier adapted to a specific set of image classes
  • however, the application does disclose the “high-level classification problem” (i.e. to distinguish photographs from graphics and texts, see paragraphs 0002 and 0046) and it discloses that 72 lowlevel features have been chosen (from among 389 features, for example, see paragraphs 0016 and 0052) to carry out the test described in paragraphs 0047 to 0053
  • background of that choice may lack detail but it still provides the general teaching that a (sub-)set of low-level features can be chosen according to general criteria (discrimination power and efficiency, column 3, lines 22 to 25) and managed in any combination (paragraph 0020) to build a classifier fulfilling a set of conditions (see e.g. paragraphs 0021/0022, 0039, 0042)

Board II (inventive step):

  • all features are assumed to contribute to the technical character of the claimed subject matter
  • general aspects of processing and pre-classifying digital images are old
  • however, the claimed method derives novelty from the use of a large library of 22 specific technical image parameters (low-level features) which are not disclosed in combination in any of the available prior art documents
  • Article 56 EPC 1973 asks for an inventive technical contribution (T 641/00-Two identities/COMVIK)
  • the following line of argument guides the skilled person in an obvious manner from the prior art to the claimed method:
    • classification of digital images for the adoption of the most suitable image-processing strategies has become “an indispensable need“, see application
    • according to D2, which may be used as a starting point, Web images are classified into photographs and graphics
    • in digital image processing, it is well-known (and inevitable) to construct a classification algorithm before it is used for classifying images
    • when constructing an algorithm for classifying digital images, it is well-known to accomplish this by way of a tree classifier using features or parameters which describe a digital image, see e.g. the prior art referred to in the application itself
    • invention mainly differs from prior art by the library of specific low-level features for improving the classification result
    • however, it is evident that all the image features which are known to describe properties of digital images are natural candidates for distinguishing images and classes of images, from each other
    • the skilled person has an expectation of improvement in that any low-level feature is prima facie suitable for discriminating image classes at least at a high level.
    • the skilled person designing a binary classification tree obviously prefers features having a great power of discriminating two classes (see e.g. D3, page 4, second paragraph)
    • the application itself presents most of its low-level features as forming part of the prior art
    • regarding the few features for which no prior art has been cited in the application, the application still conveys the impression that those features represent usual parameters for describing and analysing digital images
    • otherwise, if they were fundamentally new to the image processing person, they would have to be disclosed in much greater detail
    • –> no inventive step

Contrast enhancement/AGFA-GEVAERT – T 1019/99 – 16 June 2004

In this decision, the closest prior art is a document published about 5 years before the patent. According to the patentee, no one had worked on this document during those 5 years. In this decision, therefore, the competent Board is dealing with the question of whether an ‘old’ document can be used as the closest prior art.

Object of the Invention:

  • the patent concerns the problem of image contrast enhancement in a radiographic imaging system in which there is a large difference in dynamic range between the sensor and the imaging device
  • this is solved by decomposing the image into multiple detail images at different resolution levels (multi-scale decomposition) and filtering some resolution levels with a non-linear conversion function
  • Claim 1 differs from the closest prior art (general purpose computer) in that the non-linear conversion function is specified to be monotonically increasing, odd and to have a slope that gradually decreases with increasing argument values

Appellant (closest prior art – old document):

  • D2 cannot be taken as a starting point to arrive at the invention because, it is an isolated document that no one had worked on in the five years prior to the patent

Board (closest prior art – old document):

  • any document that is state of the art under Article 54(2) EPC may be a candidate for the closest prior art
  • the state of the art is everything made available to the public
  • the jurisprudence acknowledges, some cases where a document may not be a realistic starting point because it either relates to outdated technology, and/or is associated with such well known disadvantages that the skilled person would not even consider trying to improve on it
  • in the present case, the appellant is essentially offering an additional reason for not using D2, namely that it did not receive any attention after its publication
  • the Board does not judge that D2, published only five years before the priority date of the patent, in any way represents outdated technology, even in a fast moving area such as digital image processing
  • concerning the status of D2 as an isolated document, the Board agrees with the respondent that there may be various unknown technical or economic reasons preventing an otherwise promising approach from being adopted rapidly after its early publication

Semi-automatic answering/3M INNOVATIVE PROPERTIES – T 0755/18 – 11 December 2020

This decision is about the output of a machine learning algorithm. The output of the algorithm is more accurate here compared to the prior art. However, this is not a reason that the output automatically serves a technical effect. The output therefore does not automatically lead to non-technical features making a technical contribution via the output.

Object of the Invention:

  • the present application is concerned with the generation of billing codes to be used in medical billing, wherein billings are provided to an insurer for reimbursement
  • computer-based support systems have been developed to guide human coders through the process of generating billing codes
  • claim 1 specifies a computer-implemented method for improving the accuracy of automatically generated billing codes

Board I (inventive step):

  • a billing code is non-technical administrative data
  • generating a billing code is a cognitive task

Appellant (inventive step):

  • use of machine learning techniques to improve the accuracy of the machine output
  • invention is technical because it improved the system so that it would generate more accurate billing codes in the future

Board II (inventive step):

  • if neither the output of a learning-machine computer program nor the machine output’s accuracy contributes to a technical effect, an improvement of the machine achieved automatically through supervised learning for producing a more accurate output is not in itself a technical effect
  • in this case, the learning machine’s output is a billing code, which is non-technical administrative data
  • the accuracy of the billing code refers to “administrative accuracy” regarding, for example, whether the billing code is consistent with information represented by a spoken audio stream or a draft transcript
  • the learning machine to generate more accurate billing codes or, equivalently, improving the accuracy of the billing codes generated by the system, is as such not a technical effect.

Conclusion

Furthermore, the below figure shows according to G 1/19, point 85 and 86 how and when “technical effects” or “technical interactions” based on inter alia non-technical features may occur in the context of a computer-implemented process (the arrows in the figure above represent interactions and not abstract data). In this decision T 755/18 it was discussed whether the non-technical features contribute to the technical character of the invention via the output side and also via the technical implementation (although the latter is not discussed here in this commentary).

Equivalent Aortic Pressure/ARC SEIBERSDORF – T 0161/18 – 12 May 2020

This decision concerns an invention involving machine learning. The Board of Appeal ruled on the need to disclose training data in a patent application.

Object of the Invention:

  • use of an artificial neural network to transform the blood pressure curve measured at the periphery into the equivalent aortic pressure
  • Claim 1 differs from the closest prior art (general purpose computer) in that the transformation of the blood pressure curve measured at the periphery into the equivalent aortic pressure is carried out with the aid of an artificial neural network whose weighting values are determined by learning’

Board I (sufficiency of disclosure (Article 83 EPC)):

  • the application does not disclose which input data are suitable for training the artificial neural network according to the invention, or at least one data set suitable for solving the present technical problem
  • the training of the artificial neural network can therefore not be reworked by the person skilled in the art and the person skilled in the art can therefore not carry out the invention
  • no sufficient disclosure, since the training according to the invention cannot be carried out due to a lack of corresponding disclosure

Appellant (inventive step):

  • the use of an artificial neural network has the technical effect that the cardiac output can be determined reliably and precisely, while keeping the computing effort within reasonable limits, which enables integration into a mobile and correspondingly handy device

Board II (inventive step):

  • neither the claim nor the description contain details regarding the training of the neural network
  • the claimed neural network is therefore not adapted for the specific claimed application
  • the claimed effect is not achieved in the claimed method over the entire claimed range
  • the effect cannot therefore be considered as an improvement over the prior art when assessing the inventive step
  • the object is to provide an alternative to the method disclosed in D1
  • the use of a neural networks not only corresponds to a general trend in technology, it was also already known for the transformation of the blood pressure curve measured at the periphery into the equivalent aortic pressure
  • the subject-matter of claim 1 was therefore suggested to the skilled person by combining the teaching of D1 with his general technical knowledge or with the teaching of D8 –> no inventive step

Conclusion

  • in this decision, the distinguishing feature is based on machine learning (ML)
  • ML is data-driven and, therefore, the success of an ML invention will largely depend on the data on which it is trained
  • if there is too little suitable training data, it may not work
  • the application does not disclose any input data or data set
  • for AI patent applications, at least some effort should be made to explain:
    • what training data is used, and
    • why enough of it is available to train the ML system appropriately