OBJECTIVES: To evaluate the FeelBetter machine learning system's ability to accurately identify older patients with multimorbidity at Brigham and Women's Hospital at highest risk of medication-associated emergency department (ED) visits and hospitali...
Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews
Aug 1, 2024
BACKGROUND: Accurate and precise templating is paramount for anatomic total shoulder arthroplasty (TSA) and reverse total shoulder arthroplasty (RSA) to enhance preoperative planning, streamline surgery, and improve implant positioning. We aimed to e...
International journal of surgery (London, England)
Aug 1, 2024
BACKGROUND: In-hospital mortality following hip fractures is a significant concern, and accurate prediction of this outcome is crucial for appropriate clinical management. Nonetheless, there is a lack of effective prediction tools in clinical practic...
PRIMARY OBJECTIVE: To evaluate the accuracy of an innovative machine-learning-powered near-infrared spectroscopy (mNIRS)-based bio-optical sensitivity parameters, namely specific tissue optical index (STOI) and intracranial tissue optical index (ITOI...
International journal of medical informatics
Jul 31, 2024
BACKGROUND: Atrial fibrillation (AF) is common among intensive care unit (ICU) patients and significantly raises the in-hospital mortality rate. Existing scoring systems or models have limited predictive capabilities for AF patients in ICU. Our study...
INTRODUCTION: Developing accurate models for predicting the risk of 30-day readmission is a major healthcare interest. Evidence suggests that models developed using machine learning (ML) may have better discrimination than conventional statistical mo...
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Jul 31, 2024
PURPOSE: This study investigated imaging biomarkers derived from PSMA-PET acquired pre- and post-metastasis-directed therapy (MDT) to predict 2-year metastasis-free survival (MFS), which provides valuable early response assessment to improve patient ...
BACKGROUND: An artificial intelligence-based algorithm we developed, mrAI, satisfactorily segmented the rectal tumor, rectum, and mesorectum from MRI data of rectal cancer patients in an initial study. Herein, we aimed to validate mrAI using an indep...
Neuropsychiatric symptoms (NPS) and mood disorders are common in individuals with mild cognitive impairment (MCI) and increase the risk of progression to dementia. Wearable devices collecting physiological and behavioral data can help in remote, pass...
Our objective was to develop and evaluate the clinical feasibility of deep-learning-based synthetic contrast-enhanced computed tomography (DL-SynCCT) in patients designated for nonenhanced CT (NECT). We proposed a weakly supervised learning with the ...
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