AIMC Topic: Middle Aged

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Machine Learning Analysis of MicroRNA Expression Data Reveals Novel Diagnostic Biomarker for Ischemic Stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: Ischemic stroke (IS) is one of the leading causes of morbidity and mortality worldwide. Circulating microRNAs have a potential as minimally invasive biomarkers for disease prediction, diagnosis, and prognosis. In this study, we sought to ...

Accuracy of a Deep Learning System for Classification of Papilledema Severity on Ocular Fundus Photographs.

Neurology
OBJECTIVE: To evaluate the performance of a deep learning system (DLS) in classifying the severity of papilledema associated with increased intracranial pressure on standard retinal fundus photographs.

Robot-assisted laparoscopic hysterectomy for endometrial cancer in a patient with Herlyn-Werner-Wunderlich syndrome.

BMJ case reports
Herlyn-Werner-Wunderlich syndrome, a rare Mullerian duct anomaly, includes a triad of uterine didelphys, obstructed haemivagina and ipsilateral renal agenesis. A 58-year-old woman with Herlyn-Werner-Wunderlich syndrome, reported of recurrent genital ...

Automatic Detection of Thyroid and Adrenal Incidentals Using Radiology Reports and Deep Learning.

The Journal of surgical research
BACKGROUND: Computed tomography (CT) is commonly performed when evaluating trauma patients with up to 55% showing incidental findings. Current workflows to identify and inform patients are time-consuming and prone to error. Our objective was to autom...

Survival prediction and treatment optimization of multiple myeloma patients using machine-learning models based on clinical and gene expression data.

Leukemia
Multiple myeloma (MM) remains mostly an incurable disease with a heterogeneous clinical evolution. Despite the availability of several prognostic scores, substantial room for improvement still exists. Promising results have been obtained by integrati...

Quantitative assessment of inflammatory infiltrates in kidney transplant biopsies using multiplex tyramide signal amplification and deep learning.

Laboratory investigation; a journal of technical methods and pathology
Delayed graft function (DGF) is a strong risk factor for development of interstitial fibrosis and tubular atrophy (IFTA) in kidney transplants. Quantitative assessment of inflammatory infiltrates in kidney biopsies of DGF patients can reveal predicti...

"Looking Under the Hood" of Anchor-Based Assessment of Clinically Important Change: A Machine Learning Approach.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: The Global Assessment of Change (GAC) item has facilitated the interpretation of change in patient-reported outcomes, providing an anchor for computing minimally important differences. Construct validity has been documented via disease-sp...

A deep learning model for detection of cervical spinal cord compression in MRI scans.

Scientific reports
Magnetic Resonance Imaging (MRI) evidence of spinal cord compression plays a central role in the diagnosis of degenerative cervical myelopathy (DCM). There is growing recognition that deep learning models may assist in addressing the increasing volum...