AIMC Topic: Humans

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Therapeutic engagement in robot-assisted psychological interventions: A systematic review.

Clinical psychology & psychotherapy
PURPOSE: Therapeutic engagement is a key component of psychological interventions. Robot-assisted psychological interventions appear to have therapeutic benefits for service users that are challenging to engage. However, engagement with robots in rob...

Development and Validation of an Objective Scoring Tool for Robot-Assisted Partial Nephrectomy: Scoring for Partial Nephrectomy.

Journal of endourology
To develop a structured and objective scoring tool for assessment of robot-assisted partial nephrectomy (RAPN): Scoring for Partial Nephrectomy (SPaN). : RAPN was deconstructed into 6 domains by a multi-institutional panel of 10 expert robotic surge...

When unsupervised training benefits category learning.

Cognition
Humans continuously categorise inputs, but only rarely receive explicit feedback as to whether or not they are correct. This implies that they may be integrating unsupervised information together with their sparse supervised data - a form of semi-sup...

Advancing primary care with Artificial Intelligence and Machine Learning.

Healthcare (Amsterdam, Netherlands)
Primary care is the largest healthcare delivery platform in the US. Facing the Artificial Intelligence and Machine Learning technology (AI/ML) revolution, the primary care community would benefit from a roadmap revealing priority areas and opportunit...

Perceptions of the use of artificial intelligence in the diagnosis of skin cancer: an outpatient survey.

Clinical and experimental dermatology
BACKGROUND: Convolutional neural networks (artificial intelligence, AI) are rapidly appearing within the field of dermatology, with diagnostic accuracy matching that of dermatologists. As technologies become available for use by both the health profe...

Manipulation of Multiple Cell-Cell Interactions by Tunable DNA Scaffold Networks.

Angewandte Chemie (International ed. in English)
Manipulation of cell-cell interactions via cell surface engineering has potential biomedical applications in tissue engineering and cell therapy. However, manipulation of the comprehensive and multiple intercellular interactions remains a challenge a...

A literature review of machine learning algorithms for crash injury severity prediction.

Journal of safety research
INTRODUCTION: Road traffic crashes represent a major public health concern, so it is of significant importance to understand the factors associated with the increase of injury severity of its interveners when involved in a road crash. Determining suc...

A deep-learning framework for metacarpal-head cartilage-thickness estimation in ultrasound rheumatological images.

Computers in biology and medicine
OBJECTIVE: Rheumatoid arthritis (RA) is a chronic disease characterized by erosive symmetrical polyarthritis. Bone and cartilage are the main joint targets of this disease. Cartilage damage is one of the most relevant determinants of physical disabil...

Next-generation deep learning based on simulators and synthetic data.

Trends in cognitive sciences
Deep learning (DL) is being successfully applied across multiple domains, yet these models learn in a most artificial way: they require large quantities of labeled data to grasp even simple concepts. Thus, the main bottleneck is often access to super...

Prediction of coronary heart disease based on combined reinforcement multitask progressive time-series networks.

Methods (San Diego, Calif.)
Coronary heart disease is the first killer of human health. At present, the most widely used approach of coronary heart disease diagnosis is coronary angiography, a surgery that could potentially cause some physical damage to the patients, together w...