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StrabNet-CQ: an integrated deep learning framework for automated strabismus classification and quantification using ocular landmark detection.

BMC ophthalmology
BACKGROUND: Strabismus is a common ocular misalignment that can impair binocular vision if untreated. Conventional diagnosis and treatment rely on clinical prism diopter (PD) readings, which quantify deviation along with base direction. However, thes...

Enhancing explainability of random survival forests in predicting stent patency risk for malignant colonic obstruction.

BMC gastroenterology
BACKGROUND: This study aims to enhance the explainability and predictive accuracy of the Random Survival Forest (RSF) algorithm in predicting stent patency risk for patients with malignant colonic obstruction.

Segmentation of gastroesophageal reflux events using a semi-U-Net architecture with 1D/2D CNNs.

Scientific reports
U-Net has gained traction in biomedical signal processing, particularly for segmenting 1D waveforms. Building on this success, we propose a U-Net-inspired architecture that integrates both 2D and 1D CNNs to effectively learn and segment gastroesophag...

A multi stage deep learning model for accurate segmentation and classification of breast lesions in mammography.

Scientific reports
Mammography is a routine imaging technique used by radiologists to detect breast lesions, such as tumors and lumps. Precise lesion detection is critical for early treatment and diagnosis planning. Lesion detection and segmentation are still problemat...

Optimizing YOLOv11 for automated classification of breast cancer in medical images.

Scientific reports
Breast cancer diagnosis via histopathology image analysis is a complex and subjective process. While deep learning has emerged as a powerful tool for automation, achieving high accuracy across diverse cancer subtypes and magnification levels remains ...

Application of multimodal integration to develop preoperative diagnostic models for borderline and malignant ovarian tumors.

Scientific reports
Malignant ovarian tumors (MOTs) and borderline ovarian tumors (BOTs) differ in treatment strategies and prognosis. However, accurate preoperative diagnosis remains challenging, and improving diagnostic accuracy is crucial. We developed and validated ...

Programmed cell death-related genes define distinct molecular subtypes and risk profiles in hepatocellular carcinoma.

Scientific reports
Hepatocellular carcinoma (HCC) is a biologically and clinically heterogeneous malignancy, whose initiation and progression are increasingly recognized to be driven by the aberrant regulation of programmed cell death (PCD) pathways. To elucidate this ...

Artificial intelligence based sonographic differentiation between skull fractures and normal sutures in young children.

Scientific reports
Accurate differentiation between skull fractures and sutures is challenging in young children. Traditional diagnostic modalities like computed tomography involve ionizing radiation, while sonography is safer but demands expertise. This study explores...

Randomised controlled trial of VR-based observation meditation with AI coaching ('Otti') for stress reduction in university students in the United States: study protocol.

BMJ open
INTRODUCTION: Stress is a major health issue in contemporary society, and mindfulness-based approaches reduce stress and anxiety but face practical barriers to consistent practice; this protocol evaluates a Virtual Reality (VR)-based observation medi...