Artificial intelligence for prediction of treatment outcomes in breast cancer: systematic review of design, reporting standards, and bias

Breast cancer is the second leading cause of death from cancer in women [1]. Consequently, many governments and pharmaceutical companies have implemented large-scale interventional clinical trials to investigate both new therapeutic strategies and experimental compounds [2]. As a result, current breast cancer guidelines generally rely on evidence from large, randomized phase III clinical trials [2]. However, oncologists are well aware of the pitfalls associated with applying population-based data to individual patients, including challenges in predicting treatment response and prognosis at the individual level when drawing upon trial data [3].

Source: Cancer Treatment Reviews - May 19, 2022 Category: Cancer & Oncology Authors: Chiara Corti, Marisa Cobanaj, Federica Marian, Edward Christopher Dee, Maxwell R. Lloyd, Sara Marcu, Andra Dombrovschi, Giorgio Pietro Biondetti, Felipe Batalini, Leo A. Celi, Giuseppe Curigliano Source Type: research