AIMC Topic: Middle Aged

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Classification of the Clinical Images for Benign and Malignant Cutaneous Tumors Using a Deep Learning Algorithm.

The Journal of investigative dermatology
We tested the use of a deep learning algorithm to classify the clinical images of 12 skin diseases-basal cell carcinoma, squamous cell carcinoma, intraepithelial carcinoma, actinic keratosis, seborrheic keratosis, malignant melanoma, melanocytic nevu...

Applying natural language processing techniques to develop a task-specific EMR interface for timely stroke thrombolysis: A feasibility study.

International journal of medical informatics
OBJECTIVE: To reduce errors in determining eligibility for intravenous thrombolytic therapy (IVT) in stroke patients through use of an enhanced task-specific electronic medical record (EMR) interface powered by natural language processing (NLP) techn...

Optimized multi-level elongated quinary patterns for the assessment of thyroid nodules in ultrasound images.

Computers in biology and medicine
Ultrasound imaging is one of the most common visualizing tools used by radiologists to identify the location of thyroid nodules. However, visual assessment of nodules is difficult and often affected by inter- and intra-observer variabilities. Thus, a...

Multicenter review of robotic versus laparoscopic ventral hernia repair: is there a role for robotics?

Surgical endoscopy
BACKGROUND: The utilization of robotic platforms for general surgery procedures such as hernia repair is growing rapidly in the United States. A limited amount of data are available evaluating operative outcomes in comparison to standard laparoscopic...

Electrophysiological Muscle Classification Using Multiple Instance Learning and Unsupervised Time and Spectral Domain Analysis.

IEEE transactions on bio-medical engineering
OBJECTIVE: Electrophysiological muscle classification (EMC) is a crucial step in the diagnosis of neuromuscular disorders. Existing quantitative techniques are not sufficiently robust and accurate to be reliably clinically used. Here, EMC is modeled ...

The effects of robot assisted gait training on temporal-spatial characteristics of people with spinal cord injuries: A systematic review.

The journal of spinal cord medicine
CONTEXT: Robotic assisted gait training (RAGT) technology can be used as a rehabilitation tool or as an assistive device for spinal cord injured (SCI) individuals. Its impact on upright stepping characteristics of SCI individuals using treadmill or o...

GWAS-based machine learning approach to predict duloxetine response in major depressive disorder.

Journal of psychiatric research
Major depressive disorder (MDD) is one of the most prevalent psychiatric disorders and is commonly treated with antidepressant drugs. However, large variability is observed in terms of response to antidepressants. Machine learning (ML) models may be ...

Prediction of Occult Invasive Disease in Ductal Carcinoma in Situ Using Deep Learning Features.

Journal of the American College of Radiology : JACR
PURPOSE: The aim of this study was to determine whether deep features extracted from digital mammograms using a pretrained deep convolutional neural network are prognostic of occult invasive disease for patients with ductal carcinoma in situ (DCIS) o...

Predicting suicidal ideation in primary care: An approach to identify easily assessable key variables.

General hospital psychiatry
OBJECTIVE: To obtain predictors of suicidal ideation, which can also be used for an indirect assessment of suicidal ideation (SI). To create a classifier for SI based on variables of the Patient Health Questionnaire (PHQ) and sociodemographic variabl...

Interaction of Vitamin E Intake and Pro12Ala Polymorphism of PPARG with Adiponectin Levels.

Journal of nutrigenetics and nutrigenomics
BACKGROUND/AIM: One of the beneficial effects associated with vitamin E intake is the enhancement of peroxisome proliferator-activated receptor gamma (PPARγ) activity and the consequent upregulation of adiponectin expression. The aim of this study wa...