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Machine learning models for predicting in-hospital mortality from acute pancreatitis in intensive care unit.

BMC medical informatics and decision making
BACKGROUND: Acute pancreatitis (AP) represents a critical medical condition where timely and precise prediction of in-hospital mortality is crucial for guiding optimal clinical management. This study focuses on the development of advanced machine lea...

Machine learning decision support model construction for craniotomy approach of pineal region tumors based on MRI images.

BMC medical imaging
BACKGROUND: Pineal region tumors (PRTs) are rare but deep-seated brain tumors, and complete surgical resection is crucial for effective tumor treatment. The choice of surgical approach is often challenging due to the low incidence and deep location. ...

Application of AI-assisted multi-advisor system combined with BOPPPS teaching model in clinical pharmacy education.

BMC medical education
BACKGROUND: The development of clinical pharmacy in China has been relatively slow, and standardized, effective training for clinical pharmacists remains a major challenge. At present, traditional teaching methods are not conducive to cultivating cli...

Deep learning network enhances imaging quality of low-b-value diffusion-weighted imaging and improves lesion detection in prostate cancer.

BMC cancer
BACKGROUND: Diffusion-weighted imaging with higher b-value improves detection rate for prostate cancer lesions. However, obtaining high b-value DWI requires more advanced hardware and software configuration. Here we use a novel deep learning network,...

Saliva-derived transcriptomic signature for gastric cancer detection using machine learning and leveraging publicly available datasets.

Scientific reports
Saliva, a non-invasive, self-collected liquid biopsy, holds promise for early gastric cancer (GC) screening. This study aims to assess the potential of saliva as a proxy for malignant gastric transformation and its diagnostic value through transcript...

Prediction of coronary heart disease based on klotho levels using machine learning.

Scientific reports
The diagnostic accuracy for coronary heart disease (CHD) needs to be improved. Some studies have indicated that klotho protein levels upon admission comprise an independent risk factor for CHD and have clinical value for predicting CHD. This study ai...

Evaluating the effects of active social touch and robot expressiveness on user attitudes and behaviour in human-robot interaction.

Scientific reports
Touch plays a crucial role in human social interaction and emotional communication. Social touch refers to touching others in social contexts, serving purposes like greetings, affection, persuasion, and emotional regulation. Social robots are autonom...

A machine learning and centrifugal microfluidics platform for bedside prediction of sepsis.

Nature communications
Sepsis is a life-threatening organ dysfunction due to a dysfunctional response to infection. Delays in diagnosis have substantial impact on survival. Herein, blood samples from 586 in-house patients with suspected sepsis are used in conjunction with ...

Seven Opportunities for Artificial Intelligence in Primary Care Electronic Visits: Qualitative Study of Staff and Patient Views.

Annals of family medicine
PURPOSE: Increased workload associated with electronic visits (eVisits) in primary care could potentially be decreased by the use of artificial intelligence (AI); however, it is unknown whether this use of AI would be acceptable to staff and patients...

Attitudes Toward AI Usage in Patient Health Care: Evidence From a Population Survey Vignette Experiment.

Journal of medical Internet research
BACKGROUND: The integration of artificial intelligence (AI) holds substantial potential to alter diagnostics and treatment in health care settings. However, public attitudes toward AI, including trust and risk perception, are key to its ethical and e...