OBJECTIVE: To determine whether graph neural network based models of electronic health records can predict specialty consultation care needs for endocrinology and hematology more accurately than the standard of care checklists and other conventional ...
Since the introduction of ChatGPT by OpenAI in late 2022, the question of whether doctors can employ it for consultation has been a subject of debate. ChatGPT is a deep learning model trained on a vast dataset, but concerns about the reliability of i...
Our objective was to detect common barriers to post-acute care (B2PAC) among hospitalized older adults using natural language processing (NLP) of clinical notes from patients discharged home when a clinical decision support system recommended post-ac...
IMPORTANCE: Predicting short- and long-term survival of patients with cancer may improve their care. Prior predictive models either use data with limited availability or predict the outcome of only 1 type of cancer.
Robotic sacropexy (RSC) emerged in the last years as a valid alternative to the laparoscopic technique. However, the robotic approach is still limited by platform availability and concerns about cost-effectiveness. Recently, new robotic platforms jo...
In this paper, we argue that patients who are subjects of Artificial Intelligence (AI)-supported diagnosis and treatment planning should have a right to a second opinion, but also that this right should not necessarily be construed as a right to a ph...
BACKGROUND: Analysis of the distribution of amino acid types found at equivalent positions in multiple sequence alignments has found applications in human genetics, protein engineering, drug design, protein structure prediction, and many other fields...
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