Chemotherapy

Deep learning of pretreatment ascites cytopathology for platinum-resistance risk stratification in advanced epithelial ovarian cancer.

BACKGROUND: Platinum resistance is a major determinant of poor outcome in advanced epithelial ovarian cancer, yet reliable predictors available before treatment initiation remain scarce. Ascitic fluid is commonly obtained during diagnostic work-up and directly reflects the peritoneal tumour microenvironment, but its cytomorphological information has not been systematically exploited for treatment-...

AI-assisted digital breast tomosynthesis as a decision-support tool for post-neoadjuvant surgical planning in breast cancer.

PURPOSE: Accurate assessment of residual disease after neoadjuvant chemotherapy (NAC) is essential for surgical planning and prevention of incomplete excision. This study evaluated artificial intelligence (AI)-assisted digital breast tomosynthesis (DBT) as a decision-support tool for post-NAC assessment in breast cancer. METHODS: This retrospective study included 151 patients treated with NAC foll...

Application value and challenges associated with plasma cell-free DNA metagenomic sequencing technology in the diagnosis of infections in patients with hematological disorders.

In patients with hematological disorders, the high risk of complex infections caused by immune dysfunction and intensive therapies poses a major chall...

Machine learning and plasma growth differentiation factor-15 (GDF15) for early risk stratification of heart failure progression in a long-latency doxorubicin cardiomyopathy model.

BACKGROUND: Anthracycline-induced cardiotoxicity is a major cause of late heart failure (HF) in cancer survivors. Yet early identification of individu...

Deep learning-driven MRI radiomics reveals biological subtypes and predicts recurrence risk in rectal cancer.

Traditional TNM staging inadequately captures the recurrence risk of rectal cancer (RC), limiting prognostic accuracy and personalized treatment decis...

A perioperative multi-modal fusion and deep learning-based prognostic system for upper tract urothelial carcinoma: a multi-institutional study.

OBJECTIVES: Precise perioperative risk stratification for upper tract urothelial carcinoma (UTUC) is essential. We developed a multimodal prognostic m...

Automated measurement of CD8+ T-cell distribution at the tumor epithelial-stromal interface is associated with NSCLC immunotherapy benefit and transcriptomic pathways.

Whereas anti-PD-(L)1 therapies are widely used in cancer treatment, only a subset of patients achieve long-term survival. Companion diagnostics based ...

Development and evaluation of an explainable machine learning selection pipeline for predicting neoadjuvant chemoradiotherapy response in locally advanced rectal cancer.

BACKGROUND: The selection of appropriate machine learning (ML) methods for clinical research remains challenging, particularly when both predictive pe...

Counterfactual AI for Dynamic Dose Optimization with Side-Effect Constraints.

We present DoseAI, an online-updateable causal Artificial Intelligence (AI) framework for outcome prediction and dynamic dose optimization in continuo...

Multimodal imaging and artificial intelligence for response assessment to neoadjuvant therapy in breast cancer: a comprehensive review.

This narrative review explores the latest advancements in various imaging modalities combined with artificial intelligence (AI) for monitoring respons...

Machine learning-based integration develops a novel lysosome-related prognostic signature associated with prognosis and immune infiltration landscape in acute myeloid leukemia.

BACKGROUND: Lysosomes are essential for intracellular degradation and recycling, and changes in their function significantly contribute to tumor growt...

Gastrointestinal endoscopic image classification using a hybrid modified inception network and a customized vision transformer with tree growth feature selection.

The Gastrointestinal (GI) tract plays a vital role in digestion by breaking down food into essential nutrients. Disorders such as bleeding lesions, ul...

Innovative screening for OSAS in patients with head and neck cancer using the apneal application: Protocol for a prospective single-centre study.

INTRODUCTION: OSAS is a common yet underdiagnosed condition, particularly among patients with head and neck cancers (HNC). Anatomical changes caused b...

Programmable Electrohydrodynamic Printing of Pt-CNTs Nanointerfaces via In Situ Thermal Regulation for High-Fidelity Biosensing.

The accurate simultaneous detection of uric acid (UA) and dopamine (DA) remains a challenge in clinical diagnostics due to the insufficient sensitivit...

Real-World Application of a Machine Learning-Based Early Recurrence Model for Guiding Adjuvant Chemotherapy Use in Patients with Gallbladder Cancer.

BACKGROUND/AIMS: Although recent randomized controlled trials have reported the efficacy of adjuvant chemotherapy for resected biliary tract cancer, d...

Beyond surgical risk: Multidimensional predictors of postoperative arm morbidity after breast cancer treatment.

BACKGROUND: Postoperative upper-limb morbidity following breast cancer treatment is common and clinically significant, encompassing pain, functional i...

Engineered Neutrophils in Translational Medicine: Gene Editing, Nanotechnology, and AI-Driven Clinical Breakthroughs.

Engineered neutrophils, modified via advanced biotechnological tools, are emerging as pivotal agents in translational medicine. By integrating gene ed...

Nanoelectronic Detection of Opioids: Machine Learning-Powered Screening With Carbon Nanotube Field-Effect Transistor Sensor Array.

The development of inexpensive, portable, and rapid opioid screening techniques is urgently needed because of the ongoing opioid crisis in the United ...

Spatially interpretable artificial intelligence framework to tailored neoadjuvant dual HER2 blockade in HER2-positive breast cancer.

Neoadjuvant dual HER2 blockade with trastuzumab and pertuzumab plus chemotherapy represents the current standard-of-care for HER2-positive breast canc...

Development and validation of an interpretable model for pre-chemotherapy triage of fatigue-pain-sleep disturbance burden in lung cancer.

PURPOSE: The aim of the study is to develop an interpretable machine learning model that can effectively identify patients at risk of high fatigue-pai...