AIMC Topic: Proof of Concept Study

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Retrieval-augmented generation improves precision and trust of a GPT-4 model for emergency radiology diagnosis and classification: a proof-of-concept study.

European radiology
OBJECTIVES: This study evaluated the effect of enhancing a GPT-4 model with retrieval-augmented generation on its ability to diagnose and classify traumatic injuries based on radiology reports.

Leveraging natural language processing to enhance feedback-informed group therapy: A proof of concept.

Psychotherapy (Chicago, Ill.)
Group therapy has evolved as a powerful therapeutic approach, facilitating mutual support, interpersonal learning, and personal growth among members. However, the complexity of studying communication dynamics, emotional expressions, and group interac...

Development of an artificial intelligence-based measure of therapists' skills: A multimodal proof of concept.

Psychotherapy (Chicago, Ill.)
The facilitative interpersonal skills (FIS) task is a performance-based task designed to assess clinicians' capacity for facilitating a collaborative relationship. Performance on FIS is a robust clinician-level predictor of treatment outcomes. Howeve...

Prediction of pink esthetic score using deep learning: A proof of concept.

Journal of dentistry
OBJECTIVES: This study aimed to develop a deep learning (DL) model for the predictive esthetic evaluation of single-implant treatments in the esthetic zone.

Predicting admission for fall-related injuries in older adults using artificial intelligence: A proof-of-concept study.

Geriatrics & gerontology international
AIM: Pre-injury frailty has been investigated as a tool to predict outcomes of older trauma patients. Using artificial intelligence principles of machine learning, we aimed to identify a "signature" (combination of clinical variables) that could pred...

Two-Layer Retrieval-Augmented Generation Framework for Low-Resource Medical Question Answering Using Reddit Data: Proof-of-Concept Study.

Journal of medical Internet research
BACKGROUND: The increasing use of social media to share lived and living experiences of substance use presents a unique opportunity to obtain information on side effects, use patterns, and opinions on novel psychoactive substances. However, due to th...

Leveraging Machine Learning to Identify Subgroups of Misclassified Patients in the Emergency Department: Multicenter Proof-of-Concept Study.

Journal of medical Internet research
BACKGROUND: Hospitals use triage systems to prioritize the needs of patients within available resources. Misclassification of a patient can lead to either adverse outcomes in a patient who did not receive appropriate care in the case of undertriage o...

Development of two machine learning models to predict conversion from primary HER2-0 breast cancer to HER2-low metastases: a proof-of-concept study.

ESMO open
BACKGROUND: HER2-low expression has gained clinical relevance in breast cancer (BC) due to the availability of anti-HER2 antibody-drug conjugates for patients with HER2-low metastatic BC. The well-reported instability of HER2-low status during diseas...

Deep learning and radiomics-based vascular calcification characterization in dental cone beam computed tomography as a predictive tool for cardiovascular disease: a proof-of-concept study.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVES: This study evaluated an automated deep learning method for detecting calcifications in the extracranial and intracranial carotid arteries and vertebral arteries in cone beam computed tomography (CBCT) scans. Additionally, a model utilizin...