AI Medical Compendium Topic

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Machine Learning of Physiologic Waveforms and Electronic Health Record Data: A Large Perioperative Data Set of High-Fidelity Physiologic Waveforms.

Critical care clinics
Perioperative morbidity and mortality are significantly associated with both static and dynamic perioperative factors. The studies investigating static perioperative factors have been reported; however, there are a limited number of previous studies ...

AI-clinician collaboration via disagreement prediction: A decision pipeline and retrospective analysis of real-world radiologist-AI interactions.

Cell reports. Medicine
Clinical decision support tools can improve diagnostic performance or reduce variability, but they are also subject to post-deployment underperformance. Although using AI in an assistive setting offsets many concerns with autonomous AI in medicine, s...

APPRAISE-AI Tool for Quantitative Evaluation of AI Studies for Clinical Decision Support.

JAMA network open
IMPORTANCE: Artificial intelligence (AI) has gained considerable attention in health care, yet concerns have been raised around appropriate methods and fairness. Current AI reporting guidelines do not provide a means of quantifying overall quality of...

Risk factors and clinical significance of subcutaneous emphysema after robot-assisted laparoscopic rectal surgery: a single-center experience.

Journal of robotic surgery
Subcutaneous emphysema (SE) is a complication of laparoscopic surgery, potentially resulting in severe respiratory failure. No reports to date have focused on SE during robot-assisted (RA) rectal surgery. We aimed to reveal the risk factors and clini...

DeepARV: ensemble deep learning to predict drug-drug interaction of clinical relevance with antiretroviral therapy.

NPJ systems biology and applications
Drug-drug interaction (DDI) may result in clinical toxicity or treatment failure of antiretroviral therapy (ARV) or comedications. Despite the high number of possible drug combinations, only a limited number of clinical DDI studies are conducted. Com...

Linking Protein Stability to Pathogenicity: Predicting Clinical Significance of Single-Missense Mutations in Ocular Proteins Using Machine Learning.

International journal of molecular sciences
Understanding the effect of single-missense mutations on protein stability is crucial for clinical decision-making and therapeutic development. The impact of these mutations on protein stability and 3D structure remains underexplored. Here, we develo...

Artificial intelligence-based spatial analysis of tertiary lymphoid structures and clinical significance for endometrial cancer.

Cancer immunology, immunotherapy : CII
With the incorporation of immune checkpoint inhibitors into the treatment of endometrial cancer (EC), a deeper understanding of the tumor immune microenvironment is critical. Tertiary lymphoid structures (TLSs) are considered favorable prognostic fac...

The clinical significance of an AI-based assumption model for neurocognitive diseases using a novel dual-task system.

Scientific reports
Dual-task composed of gait or stepping tasks combined with cognitive tasks has been well-established as valuable tools for detecting neurocognitive disorders such as mild cognitive impairment and early-stage Alzheimer's disease. We previously develop...