AIMC Topic: Female

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ChatGPT-4 vs. multi-disciplinary tumor board decisions for the therapeutic management of primary laryngeal cancer.

Acta oto-laryngologica
BACKGROUND: Artificial intelligence-based clinical decision support systems are promising tools for addressing the increasing complexity of oncological data and treatment. However, the integration and validation of models such as ChatGPT within multi...

Neural Network-based Automated Classification of 18 F-FDG PET/CT Lesions and Prognosis Prediction in Nasopharyngeal Carcinoma Without Distant Metastasis.

Clinical nuclear medicine
PURPOSE: To evaluate the diagnostic performance of the PET Assisted Reporting System (PARS) in nasopharyngeal carcinoma (NPC) patients without distant metastasis, and to investigate the prognostic significance of the metabolic parameters.

Effectiveness of AI-driven interventions in glycemic control: A systematic review and meta-analysis of randomized controlled trials.

Primary care diabetes
This systematic review aims to assess the effectiveness of AI-Driven Decision Support Systems in improving glycemic control, measured by Time in Range (TIR) and HbA1c levels, in patients with diabetes. Included studies were randomized controlled tria...

Data-Driven Analysis of Short- and Long-Term Outcomes of Simulation, Nasal Hump Reduction, and Rasping in Open Rhinoplasty for Nasal Dorsum Correction.

Ear, nose, & throat journal
PURPOSE: This study aims to highlight the significance of performing simulations, nasal hump reduction, and rasping in open-technique rhinoplasty for the nasal dorsum. The research utilizes data science methodologies for a thorough examination of the...

Intra- and Peritumoral Radiomics Based on Ultrasound Images for Preoperative Differentiation of Follicular Thyroid Adenoma, Carcinoma, and Follicular Tumor With Uncertain Malignant Potential.

Ultrasound in medicine & biology
OBJECTIVE: Differentiating between follicular thyroid adenoma (FTA), carcinoma (FTC), and follicular tumor with uncertain malignant potential (FT-UMP) remains challenging due to their overlapping ultrasound characteristics. This retrospective study a...

Deep learning for early detection of chronic kidney disease stages in diabetes patients: A TabNet approach.

Artificial intelligence in medicine
Chronic kidney disease (CKD) poses a significant risk for diabetes patients, often leading to severe complications. Early and accurate CKD stage detection is crucial for timely intervention. However, it remains challenging due to its asymptomatic pro...

Optimization of guidelines for Risk Of Recurrence/Prosigna testing using a machine learning model: a Swedish multicenter study.

Breast (Edinburgh, Scotland)
PURPOSE: Gene expression profiles are used for decision making in the adjuvant setting in hormone receptor-positive, HER2-negative (HR+/HER2-) breast cancer. While algorithms to optimize testing exist for RS/Oncotype Dx, no such efforts have focused ...

Application of artificial intelligence-based three dimensional digital reconstruction technology in precision treatment of complex total hip arthroplasty.

International orthopaedics
PURPOSE: To evaluate the predictive ability of AI HIP in determining the size and position of prostheses during complex total hip arthroplasty (THA). Additionally, it investigates the factors influencing the accuracy of preoperative planning predicti...

Psychological First Aid by AI: Proof-of-Concept and Comparative Performance of ChatGPT-4 and Gemini in Different Disaster Scenarios.

Journal of clinical psychology
OBJECTIVE: This study aimed to evaluate the performance and proof-of-concept of psychological first aid (PFA) provided by two AI chatbots, ChatGPT-4 and Gemini.

Predicting Knee Osteoarthritis Severity from Radiographic Predictors: Data from the Osteoarthritis Initiative.

Annals of biomedical engineering
PURPOSE: In knee osteoarthritis (KOA) treatment, preventive measures to reduce its onset risk are a key factor. Among individuals with radiographically healthy knees, however, future knee joint integrity and condition cannot be predicted by clinicall...