AIMC Topic: Cohort Studies

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Mood Prediction of Patients With Mood Disorders by Machine Learning Using Passive Digital Phenotypes Based on the Circadian Rhythm: Prospective Observational Cohort Study.

Journal of medical Internet research
BACKGROUND: Virtually, all organisms on Earth have their own circadian rhythm, and humans are no exception. Circadian rhythms are associated with various human states, especially mood disorders, and disturbance of the circadian rhythm is known to be ...

Generating automated kidney transplant biopsy reports combining molecular measurements with ensembles of machine learning classifiers.

American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
We previously reported a system for assessing rejection in kidney transplant biopsies using microarray-based gene expression data, the Molecular Microscope Diagnostic System (MMDx). The present study was designed to optimize the accuracy and stabilit...

Natural language processing of radiology reports for identification of skeletal site-specific fractures.

BMC medical informatics and decision making
BACKGROUND: Osteoporosis has become an important public health issue. Most of the population, particularly elderly people, are at some degree of risk of osteoporosis-related fractures. Accurate identification and surveillance of patient populations w...

Automated tumour budding quantification by machine learning augments TNM staging in muscle-invasive bladder cancer prognosis.

Scientific reports
Tumour budding has been described as an independent prognostic feature in several tumour types. We report for the first time the relationship between tumour budding and survival evaluated in patients with muscle invasive bladder cancer. A machine lea...

Non-invasive assessment of NAFLD as systemic disease-A machine learning perspective.

PloS one
BACKGROUND & AIMS: Current non-invasive scores for the assessment of severity of non-alcoholic fatty liver disease (NAFLD) and identification of patients with non-alcoholic steatohepatitis (NASH) have insufficient performance to be included in clinic...

Can We Accurately Identify Peritoneal Metastases Based on Their Appearance? An Assessment of the Current Practice of Intraoperative Gastrointestinal Cancer Staging.

Annals of surgical oncology
BACKGROUND: Peritoneal lesions are common findings during operative abdominal cancer staging. The decision to perform biopsy is made subjectively by the surgeon, a practice the authors hypothesized to be imprecise. This study aimed to describe optica...

Visual network alterations in brain functional connectivity in chronic low back pain: A resting state functional connectivity and machine learning study.

NeuroImage. Clinical
Chronic low back pain (cLBP) is associated with widespread functional and structural changes in the brain. This study aims to investigate the resting state functional connectivity (rsFC) changes of visual networks in cLBP patients and the feasibility...

Assessment of a Deep Learning Model Based on Electronic Health Record Data to Forecast Clinical Outcomes in Patients With Rheumatoid Arthritis.

JAMA network open
IMPORTANCE: Knowing the future condition of a patient would enable a physician to customize current therapeutic options to prevent disease worsening, but predicting that future condition requires sophisticated modeling and information. If artificial ...