AIMC Topic: Humans

Clear Filters Showing 11931 to 11940 of 95995 articles

Using machine learning to explore the efficacy of administrative variables in prediction of subjective-wellbeing outcomes in New Zealand.

Scientific reports
The growing acknowledgment of population wellbeing as a key indicator of societal prosperity has propelled governments worldwide to devise policies aimed at improving their citizens' overall wellbeing. In New Zealand, the General Social Survey provid...

Development of weighted residual RNN model with hybrid heuristic algorithm for movement recognition framework in ambient assisted living.

Scientific reports
In healthcare applications, automatic and intelligent movement recognition systems in Ambient Assisted Living (AAL) are designed for elderly and disabled persons. The AAL provides assistance as well as secure feelings to disabled persons and elderly ...

Accuracy of machine learning methods in predicting prognosis of patients with psychotic spectrum disorders: a systematic review.

BMJ open
OBJECTIVES: We aimed to examine the predictive accuracy of functioning, relapse or remission among patients with psychotic disorders, using machine learning methods. We also identified specific features that were associated with these clinical outcom...

Real-World Insights Into Dementia Diagnosis Trajectory and Clinical Practice Patterns Unveiled by Natural Language Processing: Development and Usability Study.

JMIR aging
BACKGROUND: Understanding the dementia disease trajectory and clinical practice patterns in outpatient settings is vital for effective management. Knowledge about the path from initial memory loss complaints to dementia diagnosis remains limited.

Comparison of a Novel Machine Learning-Based Clinical Query Platform With Traditional Guideline Searches for Hospital Emergencies: Prospective Pilot Study of User Experience and Time Efficiency.

JMIR human factors
BACKGROUND: Emergency and acute medicine doctors require easily accessible evidence-based information to safely manage a wide range of clinical presentations. The inability to find evidence-based local guidelines on the trust's intranet leads to info...

Reporting Quality of AI Intervention in Randomized Controlled Trials in Primary Care: Systematic Review and Meta-Epidemiological Study.

Journal of medical Internet research
BACKGROUND: The surge in artificial intelligence (AI) interventions in primary care trials lacks a study on reporting quality.

Deep learning-based Intraoperative MRI reconstruction.

European radiology experimental
BACKGROUND: We retrospectively evaluated the quality of deep learning (DL) reconstructions of on-scanner accelerated intraoperative MRI (iMRI) during respective brain tumor surgery.

Machine learning-derived prognostic signature integrating programmed cell death and mitochondrial function in renal clear cell carcinoma: identification of PIF1 as a novel target.

Cancer immunology, immunotherapy : CII
BACKGROUND: The pathogenesis and progression of renal cell carcinoma (RCC) involve complex programmed cell death (PCD) processes. As the powerhouse of the cell, mitochondria can influence cell death mechanisms. However, the prognostic significance of...

Continuous non-contact monitoring of neonatal activity.

BMC pediatrics
PURPOSE: Neonatal activity is an important physiological parameter in the neonatal intensive care unit (NICU). The degree of neonatal activity is associated with under and over-sedation and may also indicate the onset of disease. Activity may also ca...

Comprehensive clinical scale-based machine learning model for predicting subthalamic nucleus deep brain stimulation outcomes in Parkinson's disease.

Neurosurgical review
Parkinson's Disease (PD) is a growing burden with varied clinical manifestations and responses to Subthalamic Nucleus Deep Brain Stimulation (STN-DBS). At present, there is no effective and simple machine learning model based on comprehensive clinica...