AIMC Topic: Humans

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An unsupervised wavelet neural network model for approximating the solutions of non-linear nervous stomach model governed by tension, food and medicine.

Computer methods in biomechanics and biomedical engineering
The human stomach is a complex organ. Its role is to degrade food particles by using mechanical forces and chemical reactions in order to release nutrients. All ingested items, including our nutrition, should first pass through the stomach, making it...

Identifying multilevel predictors of trajectories of psychopathology and resilience among juvenile offenders: A machine learning approach.

Development and psychopathology
Mental ill health is more common among juvenile offenders relative to adolescents in general. Little is known about individual differences in their long-term psychological adaptation and its predictors from multiple aspects of their life. This study ...

A bi-layer model for identification of piwiRNA using deep neural learning.

Journal of biomolecular structure & dynamics
piwiRNA is a kind of non-coding RNA (ncRNA) that cannot be translated into proteins. It helps in understanding the study of gametes generation and regulation of gene expression over both transcriptional and post-transcriptional levels. piwiRNA has th...

Robotic locomotor training in a low-resource setting: a randomized pilot and feasibility trial.

Disability and rehabilitation
PURPOSE: Activity-based Training (ABT) represents the current standard of neurological rehabilitation. Robotic Locomotor Training (RLT), an innovative technique, aims to enhance rehabilitation outcomes. This study aimed to conduct a randomized pilot ...

Deep learning models for webcam eye tracking in online experiments.

Behavior research methods
Eye tracking is prevalent in scientific and commercial applications. Recent computer vision and deep learning methods enable eye tracking with off-the-shelf webcams and reduce dependence on expensive, restrictive hardware. However, such deep learning...

THA-Net: A Deep Learning Solution for Next-Generation Templating and Patient-specific Surgical Execution.

The Journal of arthroplasty
BACKGROUND: This study introduces THA-Net, a deep learning inpainting algorithm for simulating postoperative total hip arthroplasty (THA) radiographs from a single preoperative pelvis radiograph input, while being able to generate predictions either ...

Accelerated 3D MR neurography of the brachial plexus using deep learning-constrained compressed sensing.

European radiology
OBJECTIVES: To explore the use of deep learning-constrained compressed sensing (DLCS) in improving image quality and acquisition time for 3D MRI of the brachial plexus.

Effects of a comprehensive brain computed tomography deep learning model on radiologist detection accuracy.

European radiology
OBJECTIVES: Non-contrast computed tomography of the brain (NCCTB) is commonly used to detect intracranial pathology but is subject to interpretation errors. Machine learning can augment clinical decision-making and improve NCCTB scan interpretation. ...

An overview of ultrasound-derived radiomics and deep learning in liver.

Medical ultrasonography
Over the past few years, developments in artificial intelligence (AI), especially in radiomics and deep learning, have enabled the extraction of pathophysiology-related information from varied medical imaging and are progressively transforming medica...

Utility and safety of robot-assisted radical cystectomy in older patients with bladder cancer.

Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy
This study aimed to investigate the efficacy and safety of robot-assisted radical cystectomy (RARC) in older patients with bladder cancer (BCa). We reviewed the clinical and pathological records of 110 patients with BCa who underwent RARC at Gifu Un...