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Recent Patent Trial and Appeal Board Approaches to Patent Claims on Medical Technology Implementing AI
This article briefly analyzes recent Patent Trial and Appeal Board (PTAB) decisions on medical technology incorporating artificial intelligence (AI). Each decision involves reversal of a prior art rejection and contrasts with the other decisions on subject matter eligibility. The innovations at issue relate to a range of medical technologies concerning anatomical location-based machine learning models to predict pathological abnormalities, operation of a robotic surgical device prompted by an intra-operative surgical recommendation, and polygenic models to predict characteristics of individuals based on genetic variants. The decisions reveal different PTAB approaches and results that can inform prosecution and appeal strategies.
PTAB Decisions
Reversal of Prior Art Rejection, No Alice Issue
In Ex Parte Lyman, Appeal No. 2022-002753 (PTAB Sept. 25, 2023), an appeal to the PTAB involved technology relating to AI-based analysis of medical scans generated by medical imaging devices. The technology utilizes image data from a medical scan to train machine learning models based on datasets of medical scans and associated labels. The labels relate to pathological abnormality classes, such as atelectasis, effusion, mass, pneumonia, consolidation, emphysema, pleural thickening, cardiomegaly, infiltration, nodule, pneumothorax, edema, fibrosis, and hernia. In relevant part, the claims recited training a generical machine learning model based on a set of medical scan data and training a plurality of anatomical location-based machine learning models by performance of a fine tuning step on the generic machine learning model. In the claims, mutually exclusive subsets of the medical scan data are generated based on different anatomical locations. The claims further recited that, with respect to fine tuning, a subset of the medical scan data relating to an anatomical location is utilized to train a corresponding machine learning model associated with the anatomical location.
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