AIMC Topic: Humans

Clear Filters Showing 37411 to 37420 of 95995 articles

Cue: a deep-learning framework for structural variant discovery and genotyping.

Nature methods
Structural variants (SVs) are a major driver of genetic diversity and disease in the human genome and their discovery is imperative to advances in precision medicine. Existing SV callers rely on hand-engineered features and heuristics to model SVs, w...

Human-Aware Collaborative Robots in the Wild: Coping with Uncertainty in Activity Recognition.

Sensors (Basel, Switzerland)
This study presents a novel approach to cope with the human behaviour uncertainty during Human-Robot Collaboration (HRC) in dynamic and unstructured environments, such as agriculture, forestry, and construction. These challenging tasks, which often r...

Development of a patients' satisfaction analysis system using machine learning and lexicon-based methods.

BMC health services research
BACKGROUND: Patients' rights are integral to medical ethics. This study aimed to perform sentiment analysis and opinion mining on patients' messages by a combination of lexicon-based and machine learning methods to identify positive or negative comme...

A review and comparative study of cancer detection using machine learning: SBERT and SimCSE application.

BMC bioinformatics
BACKGROUND: Using visual, biological, and electronic health records data as the sole input source, pretrained convolutional neural networks and conventional machine learning methods have been heavily employed for the identification of various maligna...

Robot-assisted investigation of sensorimotor control in Parkinson's disease.

Scientific reports
Sensorimotor control (SMC) is a complex function that involves sensory, cognitive, and motor systems working together to plan, update and execute voluntary movements. Any abnormality in these systems could lead to deficits in SMC, which would negativ...

A comparative analysis of human and AI performance in forensic estimation of physical attributes.

Scientific reports
Human errors in criminal investigations have previously led to devastating miscarriages of justice. For example, flaws in forensic identification based on physical or photographic evidence are notoriously unreliable. The criminal justice system has, ...

A myoelectric digital twin for fast and realistic modelling in deep learning.

Nature communications
Muscle electrophysiology has emerged as a powerful tool to drive human machine interfaces, with many new recent applications outside the traditional clinical domains, such as robotics and virtual reality. However, more sophisticated, functional, and ...

Potentiality of algorithms and artificial intelligence adoption to improve medication management in primary care: a systematic review.

BMJ open
OBJECTIVES: The aim of this study is to investigate the effect of artificial intelligence (AI) and/or algorithms on drug management in primary care settings comparing AI and/or algorithms with standard clinical practice. Second, we evaluated what is ...

Investigation of radiomics and deep convolutional neural networks approaches for glioma grading.

Biomedical physics & engineering express
To determine glioma grading by applying radiomic analysis or deep convolutional neural networks (DCNN) and to benchmark both approaches on broader validation sets.Seven public datasets were considered: (1) low-grade glioma or high-grade glioma (369 p...

A systematic evaluation of deep learning methods for the prediction of drug synergy in cancer.

PLoS computational biology
One of the main obstacles to the successful treatment of cancer is the phenomenon of drug resistance. A common strategy to overcome resistance is the use of combination therapies. However, the space of possibilities is huge and efficient search strat...