Balancing prescriptions with constraint solvers
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Clinical guidelines are evidence-based care plans which detail the essential steps to be followed when caring for patients with a specific clinical problem, usually a chronic disease (e.g. diabetes, cardiovascular disease, chronic kidney disease, cancer, chronic obstructive pulmonary disease, and so on). Recommendations for chronic diseases include the medications (or group of medications) to be given at different stages of the treatment plan. We present an automated approach which combines constraint solvers and theorem provers to find the best solutions for treatment according to different criteria, and avoiding adverse drug reactions as much as possible. We extended the approach here to further refine the choice(s) to avoid dangerous or undesirable side effects.
Bowles , J K F & Caminati , M B 2019 , Balancing prescriptions with constraint solvers . in P Liò & P Zuliani (eds) , Automated Reasoning for Systems Biology and Medicine . Computational Biology , vol. 30 , Springer , Cham , pp. 243-267 . https://doi.org/10.1007/978-3-030-17297-8_9
Automated Reasoning for Systems Biology and Medicine
© Springer Nature Switzerland AG 2019. This work has been made available online in accordance with publisher policies or with permission from the rights holder. Permissions for further reuse of this content should be sought from the rights holder. This is the author created accepted manuscript following peer review and may differ slightly from the final published version. The published version should be used for citation purposes. The final published version of this work is available at https://doi.org/10.1007/978-3-030-17297-8_9
DescriptionFunding: UK EPSRC grant EP/M014290/1 and MRC grant MR/S003819/1.
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