AIMC Topic: Humans

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Deep learning-based detection and stage grading for optimising diagnosis of diabetic retinopathy.

Diabetes/metabolism research and reviews
AIMS: To establish an automated method for identifying referable diabetic retinopathy (DR), defined as moderate nonproliferative DR and above, using deep learning-based lesion detection and stage grading.

Deep Neural Networks for Image-Based Dietary Assessment.

Journal of visualized experiments : JoVE
Due to the issues and costs associated with manual dietary assessment approaches, automated solutions are required to ease and speed up the work and increase its quality. Today, automated solutions are able to record a person's dietary intake in a mu...

Requirements and reliability of AI in the medical context.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
The digital information age has been a catalyst in creating a renewed interest in Artificial Intelligence (AI) approaches, especially the subclass of computer algorithms that are popularly grouped into Machine Learning (ML). These methods have allowe...

Interaction of Indirect and Hyperdirect Pathways on Synchrony and Tremor-Related Oscillation in the Basal Ganglia.

Neural plasticity
Low-frequency oscillatory activity (3-9 Hz) and increased synchrony in the basal ganglia (BG) are recognized to be crucial for Parkinsonian tremor. However, the dynamical mechanism underlying the tremor-related oscillations still remains unknown. In ...

Automatic Classification of Hepatic Cystic Echinococcosis Using Ultrasound Images and Deep Learning.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
BACKGROUND: Hepatic cystic echinococcosis is the main form of hepatic echinococcosis, which is a life-threatening liver disease caused by parasites that requires a precise diagnosis and proper treatment.

Application of artificial intelligence-based computer-assisted diagnosis on synthetic mammograms from breast tomosynthesis: comparison with digital mammograms.

European radiology
OBJECTIVE: To compare the diagnostic agreement and performances of synthetic and conventional mammograms when artificial intelligence-based computer-assisted diagnosis (AI-CAD) is applied.

Robot-Assisted Cystectomy and Ileal Conduit for Neurogenic Bladder: Comparison of Extracorporeal Intracorporeal Urinary Diversion.

Journal of endourology
The aim of the present study was to compare the perioperative outcomes of extracorporeal (EXTRA) intracorporeal (INTRA) urinary diversion in patients undergoing robotic cystectomy and ileal conduit for neurogenic bladder. All consecutive patients ...

Applications of artificial intelligence in cardiovascular imaging.

Nature reviews. Cardiology
Research into artificial intelligence (AI) has made tremendous progress over the past decade. In particular, the AI-powered analysis of images and signals has reached human-level performance in many applications owing to the efficiency of modern mach...

Improving glomerular filtration rate estimation by semi-supervised learning: a development and external validation study.

International urology and nephrology
BACKGROUND: Accurate estimating glomerular filtration rate (GFR) is crucial both in clinical practice and epidemiological survey. We incorporated semi-supervised learning technology to improve GFR estimation performance.

Performance of Deep Learning and Genitourinary Radiologists in Detection of Prostate Cancer Using 3-T Multiparametric Magnetic Resonance Imaging.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Several deep learning-based techniques have been developed for prostate cancer (PCa) detection using multiparametric magnetic resonance imaging (mpMRI), but few of them have been rigorously evaluated relative to radiologists' performance ...