AIMC Topic: Adult

Clear Filters Showing 1841 to 1850 of 14447 articles

GLEAM: A multimodal deep learning framework for chronic lower back pain detection using EEG and sEMG signals.

Computers in biology and medicine
Low Back Pain (LBP) is the most prevalent musculoskeletal condition worldwide and a leading cause of disability, significantly affecting mobility, work productivity, and overall quality of life. Due to its high prevalence and substantial economic bur...

How Can Robotic Devices Help Clinicians Determine the Treatment Dose for Post-Stroke Arm Paresis?

Sensors (Basel, Switzerland)
Upper limb training dose after stroke is usually quantified by time and repetitions. This study analyzed upper limb motor training dose in stroke participants (N = 36) using a more comprehensive approach. Participants, classified by initial motor sev...

Perspectives on Using Artificial Intelligence to Derive Social Determinants of Health Data From Medical Records in Canada: Large Multijurisdictional Qualitative Study.

Journal of medical Internet research
BACKGROUND: Data on the social determinants of health could be used to improve care, support quality improvement initiatives, and track progress toward health equity. However, this data collection is not widespread. Artificial intelligence (AI), spec...

Preoperative multiclass classification of thymic mass lesions based on radiomics and machine learning.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Apart from rare cases such as lymphomas, germ cell tumors, neuroendocrine neoplasms, and thymic hyperplasia, thymic mass lesions (TMLs) are typically categorized into cysts, and thymomas. However, the classification results cannot be dete...

AI anxiety and knowledge payment: the roles of perceived value and self-efficacy.

BMC psychology
BACKGROUND: The integration of Artificial Intelligence (AI) into daily life raises significant challenges and uncertainties, notably concerning job security and skill relevance. This has led to the emergence of 'AI anxiety'-a stress response to poten...

Combined effects and timing of robotic training and botulinum toxin on upper limb spasticity and motor function: a single‑blinded randomized controlled pilot study.

Journal of neuroengineering and rehabilitation
BACKGROUND: This study aimed to evaluate the combined effects of robotic training (RT) and botulinum toxin (BTX) injections on motor function and spasticity in individuals with post-stroke upper limb spasticity (ULS). We also sought to investigate th...

Application of the random forest algorithm to predict skilled birth attendance and identify determinants among reproductive-age women in 27 Sub-Saharan African countries; machine learning analysis.

BMC public health
INTRODUCTION: Maternal mortality refers to a mother's death owing to complications arising from childbirth or pregnancy. This issue is a forefront public health challenge around the globe which is pronounced in low- and middle-income countries, parti...

Circulating CCN6/WISP3 in type 2 diabetes mellitus patients and its correlation with insulin resistance and inflammation: statistical and machine learning analyses.

BMC medical informatics and decision making
INTRODUCTION: Cellular Communication Network Factor 6 (CCN6) is an adipokine whose production undergoes significant alterations in metabolic disorders. Given the well-established link between obesity-induced adipokine dysfunction and the development ...

Development and validation of a machine learning model for predicting intrapartum fever using pre-labor analgesia clinical indicators: a multicenter retrospective study.

BMC pregnancy and childbirth
BACKGROUND: Labor anesthesia is commonly used for pain relief during labor, but it can increase the risk of intrapartum fever. Currently, there are no reliable tools to predict which parturients might develop fever before labor anesthesia. The predic...

Artificial intelligence for breast cancer screening in mammography (AI-STREAM): preliminary analysis of a prospective multicenter cohort study.

Nature communications
Artificial intelligence (AI) improves the accuracy of mammography screening, but prospective evidence, particularly in a single-read setting, remains limited. This study compares the diagnostic accuracy of breast radiologists with and without AI-base...