AIMC Topic: Artificial Intelligence

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Acromegaly facial changes analysis using last generation artificial intelligence methodology: the AcroFace system.

Pituitary
PURPOSE: To describe the development of the AcroFace system, an AI-based system for early detection of acromegaly, based on facial photographs analysis.

Artificial intelligence-powered four-fold upscaling of human brain synthetic metabolite maps.

The Journal of international medical research
ObjectiveCompared with anatomical magnetic resonance imaging modalities, metabolite images from magnetic resonance spectroscopic imaging often suffer from low quality and detail due to their larger voxel sizes. Conventional interpolation techniques a...

Bioanalysis of antihypertensive drugs by LC-MS: a fleeting look at the regulatory guidelines and artificial intelligence.

Bioanalysis
Hypertension is a multifaceted cardiovascular disease, a significant risk factor for stroke, heart attack, heart failure, and renal damage. An essential phase in the drug development process is the exploration of effective bioanalytical approaches to...

Use of ChatGPT for patient education involving HPV-associated oropharyngeal cancer.

American journal of otolaryngology
OBJECTIVE: This study aims to investigate the ability of ChatGPT to generate reliably accurate responses to patient-based queries specifically regarding oropharyngeal squamous cell carcinoma (OPSCC) of the head and neck.

Artificial Intelligence in rehabilitation: A narrative review on advancing patient care.

Rehabilitacion
Artificial Intelligence (AI) is revolutionizing rehabilitation by enabling data-driven, personalized, and effective patient care. AI systems analyze patterns, predict outcomes, and adapt treatments to individual needs, empowering clinicians to delive...

Artificial intelligence prediction model for readmission after DIEP flap breast reconstruction based on NSQIP data.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
BACKGROUND: Readmissions following deep inferior epigastric perforator (DIEP) flap breast reconstruction represent a significant healthcare burden, yet current risk prediction methods lack precision in identifying high-risk patients. We developed a m...

Breaking down data silos across companies to train genome-wide predictions: A feasibility study in wheat.

Plant biotechnology journal
Big data, combined with artificial intelligence (AI) techniques, holds the potential to significantly enhance the accuracy of genome-wide predictions. Motivated by the success reported for wheat hybrids, we extended the scope to inbred lines by integ...

Artificial intelligence to predict cancer risk, are we there yet? A comprehensive review across cancer types.

European journal of cancer (Oxford, England : 1990)
Cancer remains the second leading cause of death worldwide, representing a substantial challenge to global health. Although traditional risk prediction models have played a crucial role in epidemiology of several cancer types, they have limitations e...

Impact of using an AI scribe on clinical documentation and clinician-patient interactions in allied health private practice: perspectives of clinicians and patients.

Musculoskeletal science & practice
BACKGROUND: The burden associated with clinical documentation can negatively impact patient care and job satisfaction amongst allied health professionals (AHPs). Digital scribes based on artificial intelligence (AI) may address these issues, but this...

Performance of the artificial intelligence-based Swiss medical assessment system versus Manchester triage system in the emergency department: A retrospective analysis.

The American journal of emergency medicine
BACKGROUND: The emergence of artificial intelligence (AI) offers new opportunities for applications in emergency medicine, including patient triage. This study evaluates the performance of the Swiss Medical Assessment System (SMASS), an AI-based deci...