首页|Oxford University Reports Findings in Machine Learning (Glass Box and Black Box Machine Learning Approaches to Exploit Compositional Descriptors of Molecules in Drug Discovery and Aid the Medicinal Chemist)
Oxford University Reports Findings in Machine Learning (Glass Box and Black Box Machine Learning Approaches to Exploit Compositional Descriptors of Molecules in Drug Discovery and Aid the Medicinal Chemist)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting originating in Oxford, United Kingdom, by NewsRx journalists, research stated, "The synthetic medicinal chemi st plays a vital role in drug discovery. Today there are AI tools to guide next syntheses, but many are ‘Black Boxes' (BB)." The news reporters obtained a quote from the research from Oxford University, "O ne learns little more than the prediction made. There are now also AI methods em phasizing visibility and ‘explainability' (thus explainable AI or XAI) that coul d help when ‘compositional data' are used, but they often still start from seemi ngly arbitrary learned weights and lack familiar probabilistic measures based on observation and counting from the outset. If probabilistic methods were used in a complementary way with BB methods and demonstrated comparable predictive powe r, they would provide guidelines about what groups to include and avoid in next syntheses and quantify the relationships in probabilistic terms. These points ar e demonstrated by blind test comparison of two main types of BB methods and a pr obabilistic ‘Glass Box' (GB) method new outside of medicine, but which appears w ell suited to the above. Because many probabilities can be involved, emphasis is on the predictive power of its simplest explanatory models. There are usually m ore inactive compounds by orders of magnitude, often a problem for machine learn ing methods."
OxfordUnited KingdomEuropeCyborgsDrugs and TherapiesEmerging TechnologiesMachine Learning
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