Chemotherapy

Ultrasound-MRI Fusion Deep Learning Radiomics Nomogram: Refining Prognostic Stratification for Triple-Negative Breast Cancer Treated With Neoadjuvant Chemotherapy.

Mammography-based artificial intelligence model for predicting axillary lymph node status after neoadjuvant therapy in breast cancer.

OBJECTIVES: Our objective is to develop a deep learning-based artificial intelligence (AI) model capable of analyzing digital mammography (DM) images to predict axillary lymph node (ALN) status subsequent to neoadjuvant therapy (NAT) in breast cancer patients. MATERIALS AND METHODS: We developed and validated an AI model for predicting post-NAT ALN status using images and clinical data of 956 inva...

[Current status and future perspectives of precision treatment for locally advanced rectal cancer].

The treatment paradigm for locally advanced rectal cancer is undergoing a fundamental transformation from the traditional fixed triad of "radiotherapy...

[Research progress in clinical pathology and molecular mechanisms of pancreatic adenosquamous carcinoma].

Pancreatic adenosquamous carcinoma (PASC) is a rare exocrine malignancy of the pancreas with an increasing incidence, histologically defined by the co...

Predicting reactive graphene edge-adsorbed Pt single-atom catalyst structures for oxygen reduction via machine learning-enhanced DFT calculations.

Single-atom platinum on graphitic materials can enhance catalysis of the oxygen reduction reaction (ORR). The local atomic structure shapes catalytic ...

MRI-driven multimodal deep learning approach for predicting pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer: A multicenter study.

OBJECTIVES: Achieving a pathological complete response (pCR) following neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal c...

Dynamic changes in serum HER2-peptide-specific autoantibodies predict response to neoadjuvant therapy in HER2-positive breast cancer.

Update on pleural mesothelioma.

PURPOSE OF REVIEW: Pleural mesothelioma remains a universally lethal cancer with a rising global burden. This underscores the need for pulmonologists ...

[Comparative observation of analgesic efficacy between liposomal bupivacaine and "cocktail" therapy following artificial intelligence-assisted direct anterior approach total hip arthroplasty: A prospective randomized controlled study].

OBJECTIVE: To compare the analgesic efficacy and safety of liposomal bupivacaine (LB) versus ropivacaine for surgical incision local anesthesia after ...

Estimate renal cell carcinoma recurrence rates using electronic health records.

BACKGROUND: Lack of readily available recurrence data has limited the use of electronic health records (EHR) for risk assessment of cancer recurrence ...

Transfer Learning and Machine Learning for Training Five-Year Survival Prognostic Models in Early Breast Cancer: Development and Validation Study.

BACKGROUND: Prognostic information is essential for decision-making in breast cancer management. In recent years, trials and clinical practice have em...

Predicting Nosocomial Infections in Hematologic Patients: A Machine Learning Model Based on Dynamic Body Temperature Trajectories.

AIMS: To identify body temperature dynamic patterns and develop a machine learning model for the early detection of nosocomial infections. DESIGN: A r...

Development and validation of a multimodal AI-agent system for prognosis analysis of bladder urothelial carcinoma.

Precise survival risk stratification for bladder urothelial carcinoma (BUC) remains a clinical challenge. We developed and validated a multimodal AI a...

Charge Au@Pt NPs combined with 3D STS-Net for adaptive and sensitized radiotherapy of hepatocellular carcinoma: Synergistic enhancement of therapeutic gain across physical and biological dimensions.

The therapeutic gain ratio (TGR) of radiotherapy for hepatocellular carcinoma (HCC) remains limited by two major barriers: insufficient precision in a...

Objective quantification of chemotherapy-induced madarosis: a pilot study of an automated computer vision pipeline for eyebrow density assessment.

Chemotherapy-induced madarosis significantly impacts patient quality of life, yet current assessment methods rely heavily on subjective grading, limit...

Integrated genomic profiling identifies predictive biomarkers for neoadjuvant therapy response in Chinese breast cancer patients.

Neoadjuvant therapy (NAT) has emerged as a standard treatment strategy for locally advanced breast cancer (BC), yet robust biomarkers for response pre...

Whole-Genome Deep Learning Predicts Chemotherapy Response in Colorectal Cancer.

Chemotherapy response in colorectal cancer (CRC) exhibits significant heterogeneity, with current clinical predictors failing to capture complex genom...

Clinical relevance of the characterisation and quantification of CD8+ T-cell infiltration in high-grade serous ovarian carcinoma using machine learning-based image analysis of dual immunostaining.

INTRODUCTION: High-grade serous carcinoma (HGSC) is the most common and aggressive subtype of ovarian cancer. Although tumour stage and complete cytor...

Challenges and Controversies in the Diagnosis and Management of Thymic Epithelial Tumors from the Thymic Tumor Subcommittee of the International Association for the Study of Lung Cancer Rare Tumors Committee.

Thymic epithelial tumors (TETs), comprising thymomas, thymic carcinomas, and thymic neuroendocrine neoplasms, are rare prevascular (anterior) mediasti...

Quantitative CT Perfusion as a prognostic biomarker for chemotherapy response in patients with pancreatic ductal adenocarcinoma.

BACKGROUND: Response evaluation of pancreatic ductal adenocarcinoma (PDAC) with routine contrast-enhanced CT (CECT) using RECIST is currently inadequa...