Chemotherapy

Machine learning-based risk modeling for safety-focused learning curve assessment in robotic left-sided colorectal cancer surgery.

The transition from laparoscopic to robotic surgery for left-sided colorectal cancer raises safety concerns during the learning curve, particularly when complex cases are preferentially selected for the robotic platform. We evaluated a machine learning-based framework for risk-adjusted safety monitoring of robotic implementation, using outcomes from an established laparoscopic program as the refer...

Integrating CAR-T therapy with PD-1/PD-L1 blockade: Mechanisms, synergy, and optimized strategies in NSCLC.

Non-small cell lung cancer (NSCLC) presents persistent challenges in immunotherapy, as the clinical benefit of programmed cell death protein 1 (PD-1) and programmed death-ligand 1 (PD-L1) inhibitors is frequently constrained by intrinsic and acquired resistance. Central contributors include impaired antigen presentation, T cell exclusion, and the accumulation of immunosuppressive populations that ...

Multi-attribute methods in antibody-drug conjugate characterization and quality control: Opportunities, challenges, and regulatory outlook.

Antibody-drug conjugates (ADCs) are complex biotherapeutics that combine the selectivity of monoclonal antibodies with the potency of cytotoxic payloa...

Comprehensive review on immunotherapy for hepatocellular carcinoma: Current status and future perspectives.

Hepatocellular carcinoma (HCC), the most common form of primary liver cancer, remains a major global health concern due to its high incidence and mort...

Cost-effectiveness analysis of artificial intelligence (AI) for response prediction of neoadjuvant radio(chemo)therapy in locally advanced rectal cancer (LARC) in the Netherlands.

BACKGROUND: Given the potential of artificial intelligence (AI) and the increasing importance of understanding AI's economic impact, this study aims t...

Artificial Intelligence and Trichoscopy: Can AI Distinguish Between Alopecia Areata and Lichen Planopilaris?

C2HFusion: Clinical context-driven hierarchical fusion of multimodal data for personalized and quantitative prognostic assessment in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy. Accurate prognostic modeling enables reliable risk stratification to identi...

Machine learning assisted raman spectroscopy for the classification of ovarian cancer cells.

Ovarian cancer is one of the most lethal gynecological malignancies, asymptomatic early progression, ineffective screening, and high histological hete...

Machine Learning-Based Prediction Model for Delayed Chemotherapy-Induced Nausea and Vomiting in Pediatric Cancer: A Prospective Cohort Study.

BACKGROUND: Delayed chemotherapy-induced nausea and vomiting (CINV) in pediatric oncology patients is currently under-recognized. This study aims to d...

Building a national repository of dural-based lesions: clinical, pathological, and demographic insights from the Indian population.

BACKGROUND: Meningiomas are the most common dural-based intracranial tumors, yet Indian literature is predominantly composed of limited single-center ...

Chemo-prAIdict Breast: A deep learning solution for predicting residual disease on biopsies of breast cancer patients treated with neoadjuvant chemotherapy.

BACKGROUND: Predicting chemosensitivity before treatment could help tailor neoadjuvant chemotherapy (NAC) in early breast cancer (eBC). Pathological c...

Integration of histopathological characteristics by machine learning improves the prediction of neoadjuvant immunochemotherapy response in triple-negative breast cancer.

Neoadjuvant immunochemotherapy (NAIC) is a standard treatment for triple-negative breast cancer (TNBC), but there is no reliable biomarker to identify...

Automated CT-derived body composition predicts pathologic response to neoadjuvant immunotherapy in non-small cell lung cancer.

Tumor-intrinsic biomarkers alone insufficiently predict pathological complete response (pCR) to neoadjuvant immunochemotherapy (NICT) in non-small cel...

AI Clinical Decision Tools in Multidisciplinary Team Discussions for Colorectal Cancer.

Multidisciplinary team (MDT) discussions have become a cornerstone of colorectal cancer (CRC) management, integrating the expertise of surgeons, oncol...

AI-Enabled Early Detection of Chemo-Induced Cardiotoxicity Patterns Using ECG Time Series Data: A Simulated Oncology Framework.

OBJECTIVES: Chemotherapy-induced cardiotoxicity is still a major clinical problem, usually appearing subclinically before structural or symptomatic ca...

Chemotherapy-Sparing Strategies in Follicular Lymphoma: Emerging Targeted and Immune-Based Approaches.

Follicular lymphoma (FL), traditionally considered an indolent yet incurable malignancy, is experiencing a substantial evolution in its therapeutic la...

Visceral Adipose Tissue Alters Podometrics and Renal Compensation After Uninephrectomy.

INTRODUCTION: Obesity is an established risk factor for chronic kidney disease (CKD). However, excess visceral adipose tissue (VAT) termed visceral ob...

The global epidemiology of botulism outbreaks from open-source intelligence, 2017-2024.

BACKGROUND: Botulism is a rare but potentially fatal illness caused by botulinum neurotoxin, with outbreaks reported globally in humans, animals, and ...

[Neck dissection-more, less, targeted?].

Neck dissection is an essential part of surgical treatment for head and neck malignancies. In recent years, the extent of neck dissection required for...

A deep learning framework to stratify Nottingham histologic grade 2 breast tumors based on dynamic contrast-enhanced MRI.

OBJECTIVE: The Nottingham Histologic Grade (NHG) informs prognosis and treatment decisions in breast cancer, but NHG2 tumors are biologically heteroge...