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Cohort Studies

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DeepBackRib: Deep learning to understand factors associated with readmissions after rib fractures.

The journal of trauma and acute care surgery
BACKGROUND: Deep neural networks yield high predictive performance, yet obscure interpretability limits clinical applicability. We aimed to build an explainable deep neural network that elucidates factors associated with readmissions after rib fractu...

A Precision Health Service for Chronic Diseases: Development and Cohort Study Using Wearable Device, Machine Learning, and Deep Learning.

IEEE journal of translational engineering in health and medicine
This paper presents an integrated and scalable precision health service for health promotion and chronic disease prevention. Continuous real-time monitoring of lifestyle and environmental factors is implemented by integrating wearable devices, open e...

AbdomenNet: deep neural network for abdominal organ segmentation in epidemiologic imaging studies.

BMC medical imaging
BACKGROUND: Whole-body imaging has recently been added to large-scale epidemiological studies providing novel opportunities for investigating abdominal organs. However, the segmentation of these organs is required beforehand, which is time consuming,...

Machine learning models to prognose 30-Day Mortality in Postoperative Disseminated Cancer Patients.

Surgical oncology
Patients with disseminated cancer at higher risk for postoperative mortality see improved outcomes with altered clinical management. Being able to risk stratify patients immediately after their index surgery to flag high risk patients for healthcare ...

Discovering monogenic patients with a confirmed molecular diagnosis in millions of clinical notes with MonoMiner.

Genetics in medicine : official journal of the American College of Medical Genetics
PURPOSE: Cohort building is a powerful foundation for improving clinical care, performing biomedical research, recruiting for clinical trials, and many other applications. We set out to build a cohort of all monogenic patients with a definitive causa...

Deep learning analysis of clinical course of primary nephrotic syndrome: Japan Nephrotic Syndrome Cohort Study (JNSCS).

Clinical and experimental nephrology
BACKGROUND: Prognosis of nephrotic syndrome has been evaluated based on pathological diagnosis, whereas its clinical course is monitored using objective items and the treatment strategy is largely the same. We examined whether the entire natural hist...

Deep learning-based diagnosis from endobronchial ultrasonography images of pulmonary lesions.

Scientific reports
Endobronchial ultrasonography with a guide sheath (EBUS-GS) improves the accuracy of bronchoscopy. The possibility of differentiating benign from malignant lesions based on EBUS findings may be useful in making the correct diagnosis. The convolutiona...

Long-term oncologic outcomes of robot-assisted versus open radical prostatectomy for prostate cancer with seminal vesicle invasion: a multi-institutional study with a minimum 5-year follow-up.

Journal of cancer research and clinical oncology
PURPOSE: This study aimed to compare the long-term oncological outcomes of robot-assisted radical prostatectomy (RARP) vs. open radical prostatectomy (ORP) in pathologically proven prostate cancer with seminal vesicle invasion (SVI).

Predicting Mortality in Intensive Care Unit Patients With Heart Failure Using an Interpretable Machine Learning Model: Retrospective Cohort Study.

Journal of medical Internet research
BACKGROUND: Heart failure (HF) is a common disease and a major public health problem. HF mortality prediction is critical for developing individualized prevention and treatment plans. However, due to their lack of interpretability, most HF mortality ...