Using Machine Learning for Drug Discovery in IBD
Publication date
2023-05-01
Authors
Kidwai, Sarah
Rojas-Velazquez, David
Kožinec, Dora
Vaišvilas, Lukas
Perez-Pardo, Paula
Rincon, Alejandro Lopez
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Abstract
Inflammatory Bowel Disease (IBD) refers to two conditions: ulcerative colitis (UC) and Crohn disease (CD) [1]. IBD has a range of clinical symptoms including abdominal pain, diarrhoea, weight loss, constipation, and fatigue [2]. The main cause of IBD is unknown, but it is the result of a weakened immune system. The possible causes of IBD involve genetic and environmental factors. Unfortunately, with conventional diagnostic methods it is hard to predict therapeutic responsiveness of patients beforehand [3]. Genetic expression may be a valuable prediction tool to determine patient’ responsiveness to treatment.
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Citation
Kidwai, S, Rojas-Velazquez, D, Kožinec, D, Vaišvilas, L, Perez-Pardo, P & Lopez-Rincon, A 2023, Using Machine Learning for Drug Discovery in IBD. in CMBBE 2023 - 18th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering (CMBBE 2023). HAL open science, Paris, France, pp. 1-2. < https://hal.science/hal-04097613 >