Domestic Violence

Advanced Machine Learning Models for Predicting Post-Thrombolysis Hemorrhagic Transformation in Acute Ischemic Stroke Patients: A Systematic Review and Meta-Analysis.

Thrombolytic therapy is essential for acute ischemic stroke (AIS) management but poses a risk of hemorrhagic transformation (HT), necessitating accurate prediction to optimize patient care. A comprehensive search was conducted across PubMed, Web of Science, Scopus, Embase, and Google Scholar, covering studies from inception until July 10, 2024. Studies were included if they used machine learning...

[Application and prospect of machine learning in orthopaedic trauma].

OBJECTIVE: To review the current applications of machine learning in orthopaedic trauma and anticipate its future role in clinical practice.

[Application and evaluation of artificial intelligence TPS-assisted cytologic screening system in urine exfoliative cytology].

To explore the application of manual screening collaborated with the Artificial Intelligence TPS-Assisted Cytologic Screening System in urinary exfol...

[Advancements in virtual screening techniques for study of enzyme inhibitor compounds].

Enzymes are closely associated with the onset and progression of numerous diseases, making enzymes a primary target in innovative drug development. Ho...

Artificial intelligence assistance in deciding management strategies for polytrauma and trauma patients.

<b><br>Introduction:</b> Artificial intelligence (AI) is an emerging technology with vast potential for use in several fields of med...

[Application and research progress of artificial intelligence technology in trauma treatment].

OBJECTIVE: To review the application and research progress of artificial intelligence (AI) technology in trauma treatment.

Mammography Breast Cancer Screening Triage Using Deep Learning: A UK Retrospective Study.

Background Breast screening enables early detection of cancers; however, most women have normal mammograms, resulting in repetitive and resource-inten...

The use of natural language processing in detecting and predicting falls within the healthcare setting: a systematic review.

Falls are a common problem associated with significant morbidity, mortality, and economic costs. Current fall prevention policies in local healthcare ...

Development of a Machine Learning-Based Prescriptive Tool to Address Racial Disparities in Access to Care After Penetrating Trauma.

IMPORTANCE: The use of artificial intelligence (AI) in clinical medicine risks perpetuating existing bias in care, such as disparities in access to po...

Comparison of the Diagnostic Accuracy of Mammogram-based Deep Learning and Traditional Breast Cancer Risk Models in Patients Who Underwent Supplemental Screening with MRI.

Background Access to supplemental screening breast MRI is determined using traditional risk models, which are limited by modest predictive accuracy. P...

[Reflections on the Implications of the Developments in ChatGPT for Changes in Medical Education Models].

Ever since its official launch, Chat Generative Pre-Trained Transformer, or ChatGPT, a natural language processing tool driven by artificial intellige...

Artificial intelligence-supported screen reading versus standard double reading in the Mammography Screening with Artificial Intelligence trial (MASAI): a clinical safety analysis of a randomised, controlled, non-inferiority, single-blinded, screening accuracy study.

BACKGROUND: Retrospective studies have shown promising results using artificial intelligence (AI) to improve mammography screening accuracy and reduce...

iAMPCN: a deep-learning approach for identifying antimicrobial peptides and their functional activities.

Antimicrobial peptides (AMPs) are short peptides that play crucial roles in diverse biological processes and have various functional activities agains...

3-LbNets: Tri-Labeling Deep Convolutional Neural Network for the Automated Screening of Glaucoma, Glaucoma Suspect, and No Glaucoma in Fundus Images.

Early detection of glaucoma, a widespread visual disease, can prevent vision loss. Unfortunately, ophthalmologists are scarce and clinical diagnosis r...

A Deep Learning Framework for Image-Based Screening of Kawasaki Disease.

Kawasaki disease (KD) is a leading cause of acquired heart disease in children and is characterized by the presence of a combination of five clinical ...

Spatiotemporal Mammography-based Deep Learning Model for Improved Breast Cancer Risk Prediction.

Breast cancer is one of the most prevalent cancers among women. It is the second leading cause of death in cancer-related deaths. Early detection and ...

Deep learning-based detection of diabetic macular edema using optical coherence tomography and fundus images: A meta-analysis.

Diabetic macular edema (DME) is an important cause of visual impairment in the working-age group. Deep learning methods have been developed to detect ...

Automatic Identification and Segmentation of Orbital Blowout Fractures Based on Artificial Intelligence.

PURPOSE: The incidence of orbital blowout fractures (OBFs) is gradually increasing due to traffic accidents, sports injuries, and ocular trauma. Orbit...

Robot-based psychological intervention program for the prevention of child sexual abuse: An overview.

Sexual abuse of children is an important issue with severe consequences, so self-care education programs increase children's awareness, knowledge, and...

DECIDE-AI: a new reporting guideline and its relevance to artificial intelligence studies in radiology.

DECIDE-AI is a new, stage-specific reporting guideline for the early and live clinical evaluation of decision-support systems based on artificial inte...