AIMC Topic: Humans

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Classification of attention deficit hyperactivity disorder using machine learning on an EEG dataset.

Applied neuropsychology. Child
The neurodevelopmental disorder, Attention Deficit Hyperactivity Disorder (ADHD), frequently affecting youngsters, is characterized by persistent patterns of inattention, hyperactivity, and impulsivity, the etiology of which may involve a variety of ...

iTTCA-MVL: A multi-view learning model based on physicochemical information and sequence statistical information for tumor T cell antigens identification.

Computers in biology and medicine
Immunotherapy is an emerging treatment method aimed at activating the human immune system and relying on its own immune function to kill cancer cells and tumor tissues. It has the advantages of wide applicability and minimal side effects. Effective i...

Symptomatic Lymphocele After Robot-Assisted Pelvic Lymphadenectomy as Part of the Primary Surgical Treatment for Cervical and Endometrial Cancer: A Retrospective Cohort Study.

Journal of minimally invasive gynecology
STUDY OBJECTIVES: Pelvic lymph node dissection (PLND) is part of the primary treatment for early-stage cervical cancer and high-intermediate risk or high-risk endometrial cancer. Pelvic lymphocele is a postoperative complication of PLND, and when sym...

An emotion recognition method based on EWT-3D-CNN-BiLSTM-GRU-AT model.

Computers in biology and medicine
This has become a significant study area in recent years because of its use in brain-machine interaction (BMI). The robustness problem of emotion classification is one of the most basic approaches for improving the quality of emotion recognition syst...

Dyad motor learning in a wrist-robotic environment: Learning together is better than learning alone.

Human movement science
OBJECTIVE: Dyad motor practice is characterized by two learners alternating between physical and observational practice, which can lead to better motor outcomes and reduce practice time compared to physical practice alone. Robot-assisted therapy has ...

A new era is emerging at scientific user facilities.

IUCrJ
Global scientific exchange has been profoundly perturbed by the COVID-19 pandemic, altering user travel behaviours and accelerating the use of remote access. Combined with the advent of artificial intelligence (AI), these trends together can change h...

Deep learning to overcome Zernike phase-contrast nanoCT artifacts for automated micro-nano porosity segmentation in bone.

Journal of synchrotron radiation
Bone material contains a hierarchical network of micro- and nano-cavities and channels, known as the lacuna-canalicular network (LCN), that is thought to play an important role in mechanobiology and turnover. The LCN comprises micrometer-sized lacuna...

Application of Machine Learning Techniques to Development of Emergency Medical Rapid Triage Prediction Models in Acute Care.

Computers, informatics, nursing : CIN
Given the critical and complex features of medical emergencies, it is essential to develop models that enable prompt and suitable clinical decision-making based on considerable information. Emergency nurses are responsible for categorizing and priori...

Psychotherapy, artificial intelligence and adolescents: ethical aspects.

Journal of preventive medicine and hygiene
Artificial intelligence (AI) has rapidly advanced in various domains, including its application in psychotherapy. AI-powered psychotherapy tools present promising solutions for increasing accessibility to mental health care. However, the integration ...

Impact of artificial intelligence on prognosis, shared decision-making, and precision medicine for patients with inflammatory bowel disease: a perspective and expert opinion.

Annals of medicine
INTRODUCTION: Artificial intelligence (AI) is expected to impact all facets of inflammatory bowel disease (IBD) management, including disease assessment, treatment decisions, discovery and development of new biomarkers and therapeutics, as well as cl...