AIMC Topic: Humans

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Prediction of Human Organ Toxicity via Artificial Intelligence Methods.

Chemical research in toxicology
Unpredicted human organ level toxicity remains one of the major reasons for drug clinical failure. There is a critical need for cost-efficient strategies in the early stages of drug development for human toxicity assessment. At present, artificial in...

Modeling contact forces during human-robot interactions for performing activities of daily living.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
This study aims to characterize contact forces between humans and tools during activities of daily living (ADL) to provide information to a personal care robot. The study was conducted on non-impaired subjects to capture various static and dynamic fo...

Machine learning algorithms for identifying predictive variables of mortality risk following dementia diagnosis: a longitudinal cohort study.

Scientific reports
Machine learning (ML) could have advantages over traditional statistical models in identifying risk factors. Using ML algorithms, our objective was to identify the most important variables associated with mortality after dementia diagnosis in the Swe...

Discovery of senolytics using machine learning.

Nature communications
Cellular senescence is a stress response involved in ageing and diverse disease processes including cancer, type-2 diabetes, osteoarthritis and viral infection. Despite growing interest in targeted elimination of senescent cells, only few senolytics ...

A single-center experience of over 300 cases of single-incision robotic cholecystectomy comparing the da Vinci SP with the Si/Xi systems.

Scientific reports
Minimally invasive surgery is usually more beneficial than open surgeries in various fields of surgery. With the newly developed Single-Port (SP) robotic surgical system, even single-site surgery has become easier to access. We compared single-incisi...

Effect of Deep Learning Reconstruction on Evaluating Cervical Spinal Canal Stenosis With Computed Tomography.

Journal of computer assisted tomography
OBJECTIVE: Magnetic resonance imaging (MRI) is commonly used to evaluate cervical spinal canal stenosis; however, some patients are ineligible for MRI. We aimed to assess the effect of deep learning reconstruction (DLR) in evaluating cervical spinal ...

A Feasibility Study on Deep Learning Reconstruction to Improve Image Quality With PROPELLER Acquisition in the Setting of T2-Weighted Gynecologic Pelvic Magnetic Resonance Imaging.

Journal of computer assisted tomography
OBJECTIVES: Evaluate deep learning (DL) to improve the image quality of the PROPELLER (Periodically Rotated Overlapping Parallel Lines with Enhanced Reconstruction technique) for 3 T magnetic resonance imaging of the female pelvis.

Artificial intelligence applications in prostate cancer.

Prostate cancer and prostatic diseases
Artificial intelligence (AI) applications have enabled remarkable advancements in healthcare delivery. These AI tools are often aimed to improve accuracy and efficiency of histopathology assessment and diagnostic imaging interpretation, risk stratifi...

Ergonomic investigations on novel dynamic postural estimator using blaze pose and transfer learning.

Ergonomics
The aim is to develop a computer-based assessment model for novel dynamic postural evaluation using RULA. The present study proposed a camera-based, three-dimensional (3D) dynamic human pose estimation model using 'BlazePose' with a data set of 50,00...