AIMC Topic: Humans

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Machine and deep learning models for accurate detection of ischemia and scar with myocardial blood flow positron emission tomography imaging.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: Quantification of myocardial blood flow (MBF) is used for the noninvasive diagnosis of patients with coronary artery disease (CAD). This study compared traditional statistics, machine learning, and deep learning techniques in their abilit...

Robotic assessment of sensorimotor and cognitive deficits in patients with temporal lobe epilepsy.

Epilepsy & behavior : E&B
OBJECTIVE: Individuals with temporal lobe epilepsy (TLE) frequently demonstrate impairments in executive function, working memory, and/or declarative memory. It is recommended that screening for cognitive impairment is undertaken in all people newly ...

Relabeling for Indoor Localization Using Stationary Beacons in Nursing Care Facilities.

Sensors (Basel, Switzerland)
In this study, we propose an augmentation method for machine learning based on relabeling data in caregiving and nursing staff indoor localization with Bluetooth Low Energy (BLE) technology. Indoor localization is used to monitor staff-to-patient ass...

The Laboratory Diagnosis of Malaria: A Focus on the Diagnostic Assays in Non-Endemic Areas.

International journal of molecular sciences
Even if malaria is rare in Europe, it is a medical emergency and programs for its control should ensure both an early diagnosis and a prompt treatment within 24-48 h from the onset of the symptoms. The increasing number of imported malaria cases as w...

Refining mutanome-based individualised immunotherapy of melanoma using artificial intelligence.

European journal of medical research
Using the particular nature of melanoma mutanomes to develop medicines that activate the immune system against specific mutations is a game changer in immunotherapy individualisation. It offers a viable solution to the recent rise in resistance to ac...

Deep learning-based identification of eyes at risk for glaucoma surgery.

Scientific reports
To develop and evaluate the performance of a deep learning model (DLM) that predicts eyes at high risk of surgical intervention for uncontrolled glaucoma based on multimodal data from an initial ophthalmology visit. Longitudinal, observational, retro...

Comparative analysis of radiomics and deep-learning algorithms for survival prediction in hepatocellular carcinoma.

Scientific reports
To examine the comparative robustness of computed tomography (CT)-based conventional radiomics and deep-learning convolutional neural networks (CNN) to predict overall survival (OS) in HCC patients. Retrospectively, 114 HCC patients with pretherapeut...

Evaluation of deep learning-based quantitative computed tomography for opportunistic osteoporosis screening.

Scientific reports
To evaluate diagnostic efficacy of deep learning (DL)-based automated bone mineral density (BMD) measurement for opportunistic screening of osteoporosis with routine computed tomography (CT) scans. A DL-based automated quantitative computed tomograph...

A multimodal magnetoelastic artificial skin for underwater haptic sensing.

Science advances
Future exploitation of marine resources in a sustainable and eco-friendly way requires autonomous underwater robotics with human-like perception. However, the development of such intelligent robots is now impeded by the lack of adequate underwater ha...

Application of eHealth Tools in Anticoagulation Management After Cardiac Valve Replacement: Scoping Review Coupled With Bibliometric Analysis.

JMIR mHealth and uHealth
BACKGROUND: Anticoagulation management can effectively prevent complications in patients undergoing cardiac valve replacement (CVR). The emergence of eHealth tools provides new prospects for the management of long-term anticoagulants. However, there ...