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. Clinical ...

Algorithms, examples and tests for denoising, deblurring, zooming, dequantization and compressive imaging with total variation (TV) and second-order total generalized variation (TGV) regularization.

ABSTRACT: Introduction: Breast Cancer (BC) remains a significant health concern worldwide, and accurate prediction of its recurrence after surgery is vital for patient management and treatment ...

One of the biggest barriers to using AI successfully is bias, which is one of the terms we defined last time, as follows: Bias, in a general context, refers to a predisposition or inclination towards ...

Objectives: The absence of predictive markers for kidney stone recurrence poses a challenge for the clinical management of stone disease. The unpredictability of stone events is also a significant ...

This is an ASCO Meeting Abstract from the 2024 ASCO Annual Meeting I. This abstract does not include a full text component.

The automatic rule-based recurrence detection algorithm (Auto-Recur), using notes on image reading (positron emission tomography-computed tomography [PET-CT], CT, magnetic resonance imaging [MRI]), ...

Summary: The algorithm of follow-up in patients with head and neck cancer (HNC) has been prepared by a board of Polish Head Neck and Oncology Experts. The aim of this research is to focus on the ...