AIMC Topic: Humans

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[ChatGPT for use in technology-enhanced learning in anesthesiology and emergency medicine and potential clinical application of AI language models : Between hype and reality around artificial intelligence in medical use].

Die Anaesthesiologie
BACKGROUND: The utilization of AI language models in education and academia is currently a subject of research, and applications in clinical settings are also being tested. Studies conducted by various research groups have demonstrated that language ...

Artificial Intelligence Predicts Hospitalization for Acute Heart Failure Exacerbation in Patients Undergoing Myocardial Perfusion Imaging.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Heart failure (HF) is a leading cause of morbidity and mortality in the United States and worldwide, with a high associated economic burden. This study aimed to assess whether artificial intelligence models incorporating clinical, stress test, and im...

Artificial Intelligence and the National Violent Death Reporting System: A Rapid Review.

Computers, informatics, nursing : CIN
As the awareness on violent deaths from guns, drugs, and suicides emerges as a public health crisis in the United States, attempts to prevent injury and mortality through nursing research are critical. The National Violent Death Reporting System prov...

Impact of F-FDG PET Intensity Normalization on Radiomic Features of Oropharyngeal Squamous Cell Carcinomas and Machine Learning-Generated Biomarkers.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
We aimed to investigate the effects of F-FDG PET voxel intensity normalization on radiomic features of oropharyngeal squamous cell carcinoma (OPSCC) and machine learning-generated radiomic biomarkers. We extracted 1,037 F-FDG PET radiomic features q...

Identifying Main Themes in Diabetes Management Interviews Using Natural Language Processing-Based Text Mining.

Computers, informatics, nursing : CIN
This study aimed to identify the main themes from exit interviews of adult patients with type 2 diabetes after completion of a diabetes education program. Eighteen participants with type 2 diabetes completed an exit interview regarding their program ...

Machine Learning-Based Approach to Predict Last-Minute Cancellation of Pediatric Day Surgeries.

Computers, informatics, nursing : CIN
The last-minute cancellation of surgeries profoundly affects patients and their families. This research aimed to forecast these cancellations using EMR data and meteorological conditions at the time of the appointment, using a machine learning approa...

Deep learning-based multi-model prediction for disease-free survival status of patients with clear cell renal cell carcinoma after surgery: a multicenter cohort study.

International journal of surgery (London, England)
BACKGROUND: Although separate analysis of individual factor can somewhat improve the prognostic performance, integration of multimodal information into a single signature is necessary to stratify patients with clear cell renal cell carcinoma (ccRCC) ...

Development and validation of a deep learning radiomics model with clinical-radiological characteristics for the identification of occult peritoneal metastases in patients with pancreatic ductal adenocarcinoma.

International journal of surgery (London, England)
BACKGROUND: Occult peritoneal metastases (OPM) in patients with pancreatic ductal adenocarcinoma (PDAC) are frequently overlooked during imaging. The authors aimed to develop and validate a computed tomography (CT)-based deep learning-based radiomics...

Development of interpretable machine learning models for prediction of acute kidney injury after noncardiac surgery: a retrospective cohort study.

International journal of surgery (London, England)
BACKGROUND: Early identification of patients at high-risk of postoperative acute kidney injury (AKI) can facilitate the development of preventive approaches. This study aimed to develop prediction models for postoperative AKI in noncardiac surgery us...