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MAIPI: A Novel AI-Powered Prognostic Index for Mantle Cell Lymphoma Using Routine Histology
Posted inAI Hematology-Oncology news

MAIPI: A Novel AI-Powered Prognostic Index for Mantle Cell Lymphoma Using Routine Histology

Posted by MedXY By MedXY 07/12/2026
The MAIPI deep learning model offers a novel, accurate prognosis tool for mantle cell lymphoma, using standard H&E stained biopsy images, bypassing need for molecular tests or expert pathology, and enhancing risk stratification for individualized therapy.
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Predictive Power of MRI-Based Radiomic Dynamics for Pathological Complete Response in Hepatocellular Carcinoma: A Deep Learning Synthesis
Posted inClinical Updates news Oncology Radiology

Predictive Power of MRI-Based Radiomic Dynamics for Pathological Complete Response in Hepatocellular Carcinoma: A Deep Learning Synthesis

Posted by MedXY By MedXY 03/15/2026
This review evaluates how deep learning-assisted delta radiomics on MRI, combined with AFP response, provides a non-invasive, high-accuracy prediction of pathological complete response in unresectable HCC undergoing conversion immunotherapy.
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Breaking the Hardware Barrier: How Domain-Shift AI Enables Vendor-Agnostic 3D OCT Macular Disease Detection
Posted inAI news Ophthalmology

Breaking the Hardware Barrier: How Domain-Shift AI Enables Vendor-Agnostic 3D OCT Macular Disease Detection

Posted by MedXY By MedXY 02/27/2026
A multicenter study in JAMA Ophthalmology introduces a deep learning model using domain-shift technology to accurately detect macular diseases across different OCT hardware vendors, achieving high negative predictive value and establishing a robust triage system for diverse clinical settings.
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AI-Driven Prognosis: EEGSurvNet Accurately Predicts Seizure Timing From Routine EEG Data
Posted inAI Neurology news

AI-Driven Prognosis: EEGSurvNet Accurately Predicts Seizure Timing From Routine EEG Data

Posted by MedXY By MedXY 01/28/2026
Researchers developed EEGSurvNet, a deep survival model that analyzes routine EEG to predict seizure risk over two years. Outperforming clinical models, it achieved an AUROC of 0.80 at two months and showed high efficacy in patients without visible epileptiform discharges.
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Muscle-Bone Ratio: A New AI-Driven Biomarker for Anti-EGFR Response in Metastatic Colorectal Cancer
Posted inAI news Oncology

Muscle-Bone Ratio: A New AI-Driven Biomarker for Anti-EGFR Response in Metastatic Colorectal Cancer

Posted by MedXY By MedXY 01/08/2026
A deep learning-derived sarcopenia marker, the muscle-bone ratio (MBR), has been shown to predict the efficacy of anti-EGFR maintenance therapy in patients with RAS wild-type metastatic colorectal cancer, potentially identifying those who truly benefit from treatment intensification.
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Deep Learning in Otolaryngology: Promises, Performance, and Pathways to Clinical Use
Posted inAI news Otorhinolaryngology

Deep Learning in Otolaryngology: Promises, Performance, and Pathways to Clinical Use

Posted by MedXY By MedXY 11/19/2025
This critical synthesis of a 2020–2025 narrative review (327 DL studies) evaluates deep learning (DL) applications across diagnosis, prognosis, segmentation, and emerging intraoperative uses in otolaryngology and outlines practical steps for safe, equitable implementation.
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Deep Learning Predicts Glaucoma Risk via Retinal Nerve Fiber Layer Thickness from Ocular Hypertension Photographs
Posted inAI Ophthalmology Specialties

Deep Learning Predicts Glaucoma Risk via Retinal Nerve Fiber Layer Thickness from Ocular Hypertension Photographs

Posted by MedXY By MedXY 09/12/2025
Deep learning models predicting RNFL thickness from optic disc photographs can identify ocular hypertension patients at higher risk for primary open-angle glaucoma, enhancing early risk assessment and monitoring disease progression.
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  • Bridging Periodontitis and Clonal Hematopoiesis: Implications for Solid Tumor Metastasis, Clinical Trial Design, and Microbiome Dynamics
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