Objective: This study aimed to develop a machine learning–based model to predict recurrence risk after perianal abscess surgery, thereby supporting personalized follow-up and intervention strategies.

At a median follow-up of 106 months, cumulative incidence of metastasis was 4.8% in the chRCC cohort, compared to 0% in the oncocytoma and ORNLMP cohorts. Oncocytomas and oncocytic neoplasms of low ...

Development and Validation of Emoji Response Scales for Assessing Patient-Reported Outcomes The Artera multimodal AI (MMAI) platform, using digital histopathology and clinical data, was applied to ...

Artificial intelligence (AI) systems, particularly artificial neural networks, have proved to be highly promising tools for uncovering patterns in large amounts of data that would otherwise be ...

SAN FRANCISCO, Oct 22 (Reuters) - Google said it has developed a computer algorithm that points the way to practical applications for quantum computing and will be able to generate unique data for use ...

Breast cancer is the most commonly diagnosed form of cancer in the world among women, with more than 2.3 million cases a year, and continues to be one of the main causes of cancer-related mortality.

The change is part of a deal to bring TikTok under U.S. ownership to avert a looming ban. By Emmett Lindner and Lauren Hirsch The software giant Oracle will oversee the security of Americans’ data and ...

During a median follow-up of 9.0 years (IQR, 6.6-10.9), IBTR occurred in 320 patients (3.6%). The initial model, based on variables from Sanghani et al, achieved a Harrell's C-index of 0.74.

Abstract: Low-grade gliomas are infiltrative, incurable primary brain tumors that usually grow slowly and cause death. This study presents a unique low-grade glioma mathematical model and predicts the ...

Background: This study seeks to develop and validate a machine learning (ML) model for predicting atrial fibrillation (AF) recurrence at 12 months following radiofrequency catheter ablation (RFCA).