MOTIVATION: Drug repurposing (DR) is an imminent approach for identifying novel therapeutic indications for the available drugs and discovering novel drugs for previously untreatable diseases. Nowadays, DR has major attention in the pharmaceutical in...
PURPOSE: Accurate prediction of the Length of Stay (LoS) and mortality in the Intensive Care Unit (ICU) is crucial for effective hospital management, and it can assist clinicians for real-time demand capacity (RTDC) administration, thereby improving ...
Accurate gait detection is crucial in utilizing the ample health information embedded in it. Vision-based approaches for gait detection have emerged as an alternative to the exacting sensor-based approaches, but their application has been rather limi...
BACKGROUND: Although accurate identification of gender identity in the electronic health record (EHR) is crucial for providing equitable health care, particularly for transgender and gender diverse (TGD) populations, it remains a challenging task due...
A log-likelihood based co-occurrence analysis of ∼1.9 million de-identified ICD-10 codes and related short textual problem list entries generated possible term candidates at a significance level of p<0.01. These top 10 term candidates, consisting of ...
INTRODUCTION: Adequate methods to promptly translate digital health innovations for improved patient care are essential. Advances in Artificial Intelligence (AI) and Machine Learning (ML) have been sources of digital innovation and hold the promise t...
OBJECTIVE: Computer-assisted diagnostic and prognostic systems of the future should be capable of simultaneously processing multimodal data. Multimodal deep learning (MDL), which involves the integration of multiple sources of data, such as images an...
Obtaining text datasets with semantic annotations is an effortful process, yet crucial for supervised training in natural language processing (NLP). In general, developing and applying new NLP pipelines in domain-specific contexts for tasks often req...
OBJECTIVE: We developed and evaluated a novel one-shot distributed algorithm for evidence synthesis in distributed research networks with rare outcomes.
Inferring knowledge from known relationships between drugs, proteins, genes, and diseases has great potential for clinical impact, such as predicting which existing drugs could be repurposed to treat rare diseases. Incorporating key biological contex...