AIMC Topic: Humans

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The Promise and Challenges of AI Integration in Ovarian Cancer Screenings.

Reproductive sciences (Thousand Oaks, Calif.)
PURPOSE: Ovarian cancer is oftendiagnosed late due to vague symptoms, leading to poor survival rate. Improved screening tests could mitigate this issue. This narrative review examines the potential and challenges of integrating artificial intelligenc...

Enhancing quality and speed in database-free neural network reconstructions of undersampled MRI with SCAMPI.

Magnetic resonance in medicine
PURPOSE: We present SCAMPI (Sparsity Constrained Application of deep Magnetic resonance Priors for Image reconstruction), an untrained deep Neural Network for MRI reconstruction without previous training on datasets. It expands the Deep Image Prior a...

Synergistic integration of deep learning with protein docking in cardiovascular disease treatment strategies.

IUBMB life
This research delves into the exploration of the potential of tocopherol-based nanoemulsion as a therapeutic agent for cardiovascular diseases (CVD) through an in-depth molecular docking analysis. The study focuses on elucidating the molecular intera...

Artificial intelligence enhances whole-slide interpretation of PD-L1 CPS in triple-negative breast cancer: A multi-institutional ring study.

Histopathology
BACKGROUND AND AIMS: Evaluation of the programmed cell death ligand-1 (PD-L1) combined positive score (CPS) is vital to predict the efficacy of the immunotherapy in triple-negative breast cancer (TNBC), but pathologists show substantial variability i...

Pure tone audiogram classification using deep learning techniques.

Clinical otolaryngology : official journal of ENT-UK ; official journal of Netherlands Society for Oto-Rhino-Laryngology & Cervico-Facial Surgery
OBJECTIVE: Pure tone audiometry has played a critical role in audiology as the initial diagnostic tool, offering vital insights for subsequent analyses. This study aims to develop a robust deep learning framework capable of accurately classifying aud...

Usefulness of Artificial Intelligence in Traumatic Brain Injury: A Bibliometric Analysis and Mini-review.

World neurosurgery
BACKGROUND: Traumatic brain injury (TBI) has become a major source of disability worldwide, increasing the interest in algorithms that use artificial intelligence (AI) to optimize the interpretation of imaging studies, prognosis estimation, and criti...

MGDDI: A multi-scale graph neural networks for drug-drug interaction prediction.

Methods (San Diego, Calif.)
Drug-drug interaction (DDI) prediction is crucial for identifying interactions within drug combinations, especially adverse effects due to physicochemical incompatibility. While current methods have made strides in predicting adverse drug interaction...

The Use of Artificial Intelligence to Improve Readability of Otolaryngology Patient Education Materials.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: The recommended readability of health education materials is at the sixth-grade level. Artificial intelligence (AI) large language models such as the newly released ChatGPT4 might facilitate the conversion of patient-education materials at...