AIMC Topic: Humans

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Deep learning-based behavioral analysis reaches human accuracy and is capable of outperforming commercial solutions.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
To study brain function, preclinical research heavily relies on animal monitoring and the subsequent analyses of behavior. Commercial platforms have enabled semi high-throughput behavioral analyses by automating animal tracking, yet they poorly recog...

Predicting In Vitro Neurotoxicity Induced by Nanoparticles Using Machine Learning.

International journal of molecular sciences
The practice of non-testing approaches in nanoparticles hazard assessment is necessary to identify and classify potential risks in a cost effective and timely manner. Machine learning techniques have been applied in the field of nanotoxicology with e...

Robotic tests for position sense and movement discrimination in the upper limb reveal that they each are highly reproducible but not correlated in healthy individuals.

Journal of neuroengineering and rehabilitation
BACKGROUND: Robotic technologies for neurological assessment provide sensitive, objective measures of behavioural impairments associated with injuries or disease such as stroke. Previous robotic tasks to assess proprioception typically involve single...

Robot applications for autism: a comprehensive review.

Disability and rehabilitation. Assistive technology
PURPOSE: Technological advances in robotics have brought about exciting developments in different areas such as education, training, and therapy. Recent research has suggested that the robot can be even more effective in rehabilitation, therapy, and ...

Three Different Learning Curves Have an Independent Impact on Perioperative Outcomes After Robotic Partial Nephrectomy: A Comparative Analysis.

Annals of surgical oncology
BACKGROUND: Robot-assisted partial nephrectomy (RAPN) has become widely accepted, but its different underlying types of learning curves have not been comparatively analyzed to date. This study aimed to determine and compare the impact that the learni...

Supervised machine learning for the early prediction of acute respiratory distress syndrome (ARDS).

Journal of critical care
PURPOSE: Acute respiratory distress syndrome (ARDS) is a serious respiratory condition with high mortality and associated morbidity. The objective of this study is to develop and evaluate a novel application of gradient boosted tree models trained on...

Repurpose Open Data to Discover Therapeutics for COVID-19 Using Deep Learning.

Journal of proteome research
There have been more than 2.2 million confirmed cases and over 120 000 deaths from the human coronavirus disease 2019 (COVID-19) pandemic, caused by the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), in the United States alone. How...

Restored pelvic anatomy is preserved after laparoscopic and robot-assisted ventral rectopexy: MRI-based 5-year follow-up of a randomized controlled trial.

Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland
AIM: Our aim was to compare the long-term anatomical outcomes between robot-assisted ventral mesh rectopexy (RVMR) and laparoscopic ventral mesh rectopexy (LVMR) for external or internal rectal prolapse.

A deep learning system to obtain the optimal parameters for a threshold-based breast and dense tissue segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Breast cancer is the most frequent cancer in women. The Spanish healthcare network established population-based screening programs in all Autonomous Communities, where mammograms of asymptomatic women are taken with early di...