AIMC Topic: Humans

Clear Filters Showing 22431 to 22440 of 95995 articles

Deep learning-based diagnosis and survival prediction of patients with renal cell carcinoma from primary whole slide images.

Pathology
There is an urgent clinical demand to explore novel diagnostic and prognostic biomarkers for renal cell carcinoma (RCC). We proposed deep learning-based artificial intelligence strategies. The study included 1752 whole slide images from multiple cent...

Predicting Knee Joint Contact Force Peaks During Gait Using a Video Camera or Wearable Sensors.

Annals of biomedical engineering
PURPOSE: Estimating loading of the knee joint may be helpful in managing degenerative joint diseases. Contemporary methods to estimate loading involve calculating knee joint contact forces using musculoskeletal modeling and simulation from motion cap...

Artificial Intelligence and Machine Learning in Cancer Pain: A Systematic Review.

Journal of pain and symptom management
BACKGROUND/OBJECTIVES: Pain is a challenging multifaceted symptom reported by most cancer patients. This systematic review aims to explore applications of artificial intelligence/machine learning (AI/ML) in predicting pain-related outcomes and pain m...

Diagnostic performances of Claude 3 Opus and Claude 3.5 Sonnet from patient history and key images in Radiology's "Diagnosis Please" cases.

Japanese journal of radiology
PURPOSE: The diagnostic performance of large language artificial intelligence (AI) models when utilizing radiological images has yet to be investigated. We employed Claude 3 Opus (released on March 4, 2024) and Claude 3.5 Sonnet (released on June 21,...

Machine learning-assisted label-free colorectal cancer diagnosis using plasmonic needle-endoscopy system.

Biosensors & bioelectronics
Early and accurate detection of colorectal cancer (CRC) is critical for improving patient outcomes. Existing diagnostic techniques are often invasive and carry risks of complications. Herein, we introduce a plasmonic gold nanopolyhedron (AuNH)-coated...

Assessing dimensions of thought disorder with large language models: The tradeoff of accuracy and consistency.

Psychiatry research
Natural Language Processing (NLP) methods have shown promise for the assessment of formal thought disorder, a hallmark feature of schizophrenia in which disturbances to the structure, organization, or coherence of thought can manifest as disordered o...

A pre-trained language model for emergency department intervention prediction using routine physiological data and clinical narratives.

International journal of medical informatics
INTRODUCTION: The urgency and complexity of emergency room (ER) settings require precise and swift decision-making processes for patient care. Ensuring the timely execution of critical examinations and interventions is vital for reducing diagnostic e...

Integrating machine learning and biosensors in microfluidic devices: A review.

Biosensors & bioelectronics
Microfluidic devices are increasingly widespread in the literature, being applied to numerous exciting applications, from chemical research to Point-of-Care devices, passing through drug development and clinical scenarios. Setting up these microenvir...

Optimizing BenMAP health impact assessment with meteorological factor driven machine learning models.

The Science of the total environment
This study aims to address accuracy challenges in assessing air pollution health impacts using Environmental Benefits Mapping and Analysis Program (BenMap), caused by limited meteorological factor data and missing pollutant data. By employing data in...

The minimal computational substrate of fluid intelligence.

Cortex; a journal devoted to the study of the nervous system and behavior
The quantification of cognitive powers rests on identifying a behavioural task that depends on them. Such dependence cannot be assured, for the powers a task invokes cannot be experimentally controlled or constrained a priori, resulting in unknown vu...