OBJECTIVES: Few machine learning (ML) models are successfully deployed in clinical practice. One of the common pitfalls across the field is inappropriate problem formulation: designing ML to fit the data rather than to address a real-world clinical p...
PURPOSE: Understanding treatment patterns and effectiveness for patients with metastatic prostate cancer (mPCa) is dependent on accurate assessment of metastatic status. The objective was to develop a natural language processing (NLP) model for ident...
Application of Artificial Intelligence (AI) tools has recently gained interest in the fields of medical imaging and radiotherapy. Even though there have been many papers published in these domains in the last few years, clinical assessment of the pro...
Outcome modeling plays an important role in personalizing radiotherapy and finds applications in specialized areas such as adaptive radiotherapy. Conventional outcome models that are based on a simplified understanding of radiobiological effects or e...
IMPORTANCE: Selection of antiseizure medications (ASMs) for epilepsy remains largely a trial-and-error approach. Under this approach, many patients have to endure sequential trials of ineffective treatments until the "right drugs" are prescribed.
G protein-coupled receptors (GPCRs) are valuable therapeutic targets for many diseases. A central question of GPCR drug discovery is to understand what determines the agonism or antagonism of ligands that bind them. Ligands exert their action via the...
Revista espanola de enfermedades digestivas
Oct 1, 2022
Artificial intelligence (AI) systems based on machine learning have evolved in the last few years with an increasing applicability in gastrointestinal endoscopy. Thanks to AI, an image (input) can be transformed into a clinical decision (output). Alt...
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