AIMC Topic: Male

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Large Vessel Occlusion Prediction in the Emergency Department with National Institutes of Health Stroke Scale Components: A Machine Learning Approach.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Aug 15, 2021
OBJECTIVE: To determine the feasibility of using a machine learning algorithm to screen for large vessel occlusions (LVO) in the Emergency Department (ED).
Disability Evaluation Functional Status Feasibility Studies Cerebrovascular Disorders Female Middle Aged Humans Predictive Value of Tests Machine Learning Male Emergency Service, Hospital Prognosis Retrospective Studies
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Clinical evaluation of a deep-learning-based computer-aided detection system for the detection of pulmonary nodules in a large teaching hospital.

Clinical radiology Aug 14, 2021
AIM: To evaluate a deep-learning-based computer-aided detection (DL-CAD) software system for pulmonary nodule detection on computed tomography (CT) images and assess its added value in the clinical practice of a large teaching hospital.
Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Hospitals, Teaching Tomography, X-Ray Computed Middle Aged Female Lung Reproducibility of Results Deep Learning Aged Adolescent Aged, 80 and over Young Adult Humans Adult Sensitivity and Specificity Retrospective Studies Male
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Wide & Deep neural network model for patch aggregation in CNN-based prostate cancer detection systems.

Computers in biology and medicine Aug 14, 2021
Prostate cancer (PCa) is one of the most commonly diagnosed cancer and one of the leading causes of death among men, with almost 1.41 million new cases and around 375,000 deaths in 2020. Artificial Intelligence algorithms have had a huge impact on me...
Male Humans Neural Networks, Computer Prostatic Neoplasms Artificial Intelligence Algorithms
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Artificial intelligence to improve efficiency of administration of gross motor function assessment in children with cerebral palsy.

Developmental medicine and child neurology Aug 13, 2021
AIM: To create a reduced version of the 66-item Gross Motor Function Measure (rGMFM-66) using innovative artificial intelligence methods to improve efficiency of administration of the GMFM-66.
Artificial Intelligence Machine Learning Prospective Studies Retrospective Studies Humans Neural Networks, Computer Child, Preschool Child Support Vector Machine Cerebral Palsy Motor Skills Female Male Severity of Illness Index Adolescent
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Feature-fusion improves MRI single-shot deep learning detection of small brain metastases.

Journal of neuroimaging : official journal of the American Society of Neuroimaging Aug 13, 2021
BACKGROUND AND PURPOSE: To examine whether feature-fusion (FF) method improves single-shot detector's (SSD's) detection of small brain metastases on contrast-enhanced (CE) T1-weighted MRI.
Deep Learning Sensitivity and Specificity Magnetic Resonance Imaging Brain Neoplasms Male Humans Algorithms
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Development of machine learning model to detect fibrotic non-alcoholic steatohepatitis in patients with non-alcoholic fatty liver disease.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver Aug 13, 2021
Cross-Sectional Studies Male Middle Aged Non-alcoholic Fatty Liver Disease Fibrosis Humans Machine Learning Female Adult
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Accounting for symptom heterogeneity can improve neuroimaging models of antidepressant response after electroconvulsive therapy.

Human brain mapping Aug 13, 2021
Depression symptom heterogeneity limits the identifiability of treatment-response biomarkers. Whether improvement along dimensions of depressive symptoms relates to separable neural networks remains poorly understood. We build on work describing thre...
Cerebral Cortex Electroconvulsive Therapy Depressive Disorder, Major Magnetic Resonance Imaging Outcome Assessment, Health Care Neuroimaging Aged Adult Male Middle Aged Humans Machine Learning Female
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Artificial Inteligence-Based Decision for the Prediction of Cardioembolism in Patients with Chagas Disease and Ischemic Stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Aug 13, 2021
BACKGROUND: Chagas disease (CD) and ischemic stroke (IS) have a close, but poorly understood, association. There is paucity of evidence on the ideal secondary prophylaxis and etiological determination, with few cardioembolic patients being identified...
Artificial Intelligence Decision Support Techniques Retrospective Studies Age Factors Humans Embolic Stroke Predictive Value of Tests Male Electronic Health Records Ischemic Stroke Chagas Disease Middle Aged Recurrence Female Risk Assessment Risk Factors Brazil Aged
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A machine learning approach identifies 5-ASA and ulcerative colitis as being linked with higher COVID-19 mortality in patients with IBD.

Scientific reports Aug 13, 2021
Inflammatory bowel diseases (IBD), namely Crohn's disease (CD) and ulcerative colitis (UC) are chronic inflammation within the gastrointestinal tract. IBD patient conditions and treatments, such as with immunosuppressants, may result in a higher risk...
Male Middle Aged Infant Adolescent Aged Aged, 80 and over Young Adult Adult Mesalamine Sulfasalazine Child, Preschool Child United States Anti-Inflammatory Agents, Non-Steroidal Humans Machine Learning Inflammatory Bowel Diseases Female Infant, Newborn COVID-19 Databases, Factual
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Deep learning-based gene selection in comprehensive gene analysis in pancreatic cancer.

Scientific reports Aug 13, 2021
The selection of genes that are important for obtaining gene expression data is challenging. Here, we developed a deep learning-based feature selection method suitable for gene selection. Our novel deep learning model includes an additional feature-s...
Humans Female Aged Deep Learning Survival Analysis Gene Expression Regulation, Neoplastic Male Pancreas Pancreatic Neoplasms Middle Aged Kaplan-Meier Estimate Carcinoma, Pancreatic Ductal Transcriptome Genes, Neoplasm Case-Control Studies
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