AIMC Topic: Humans

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Mobile service robots for the operating room wing: balancing cost and performance by optimizing robotic fleet size and composition.

International journal of computer assisted radiology and surgery
PURPOSE: Integrating fleets of mobile service robots into the operating room wing (OR wing) has the potential to help overcome staff shortages and reduce the amount of dull or unhealthy tasks for humans. However, the OR wing has been little studied i...

Flexible control as surrogate reward or dynamic reward maximization.

Cognition
The utility of a given experience, like interacting with a particular friend or tasting a particular food, fluctuates continually according to homeostatic and hedonic principles. Consequently, to maximize reward, an individual must be able to escape ...

RCMNet: A deep learning model assists CAR-T therapy for leukemia.

Computers in biology and medicine
Acute leukemia is a type of blood cancer with a high mortality rate. Current therapeutic methods include bone marrow transplantation, supportive therapy, and chemotherapy. Although a satisfactory remission of the disease can be achieved, the risk of ...

AntiMF: A deep learning framework for predicting anticancer peptides based on multi-view feature extraction.

Methods (San Diego, Calif.)
In recent years, anticancer peptides have emerged as a new viable option in cancer therapy, with the ability to overcome the considerable side effects and poor outcomes of standard cancer therapies. Accurate anticancer peptide identification can faci...

Assessment of deep learning pose estimates for sports collision tracking.

Journal of sports sciences
Injury assessment during sporting collisions requires estimation of the associated kinematics. While marker-based solutions are widely accepted as providing accurate and reliable measurements, setup times are lengthy and it is not always possible to ...

Recommendations on compiling test datasets for evaluating artificial intelligence solutions in pathology.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Artificial intelligence (AI) solutions that automatically extract information from digital histology images have shown great promise for improving pathological diagnosis. Prior to routine use, it is important to evaluate their predictive performance ...

Comparison of physician and artificial intelligence-based symptom checker diagnostic accuracy.

Rheumatology international
Symptom checkers are increasingly used to assess new symptoms and navigate the health care system. The aim of this study was to compare the accuracy of an artificial intelligence (AI)-based symptom checker (Ada) and physicians regarding the presence/...

Deep learning artificial intelligence framework for multiclass coronary artery disease prediction using combination of conventional risk factors, carotid ultrasound, and intraplaque neovascularization.

Computers in biology and medicine
OBJECTIVE: Cardiovascular disease (CVD) is a major healthcare challenge and therefore early risk assessment is vital. Previous assessment techniques use either "conventional CVD risk calculators (CCVRC)" or machine learning (ML) paradigms. These tech...

Image level detection of large vessel occlusion on 4D-CTA perfusion data using deep learning in acute stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: Automated image-level detection of large vessel occlusions (LVO) could expedite patient triage for mechanical thrombectomy. A few studies have previously attempted LVO detection using artificial intelligence (AI) on CT angiography (CTA) i...

Prediction of daily mean and one-hour maximum PM concentrations and applications in Central Mexico using satellite-based machine-learning models.

Journal of exposure science & environmental epidemiology
BACKGROUND: Machine-learning algorithms are becoming popular techniques to predict ambient air PM concentrations at high spatial resolutions (1 × 1 km) using satellite-based aerosol optical depth (AOD). Most machine-learning models have aimed to pred...