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http://dx.doi.org/10.1097/j.pain.0000000000003788 | DOI Listing |
Ann Surg Oncol
September 2025
HepatoBiliaryPancreatic Surgery, AOU Careggi, Department of Experimental and Clinical Medicine (DMSC), University of Florence, Florence, Italy.
Purpose: To build computed tomography (CT)-based radiomics models, with independent external validation, to predict recurrence and disease-specific mortality in patients with colorectal liver metastases (CRLM) who underwent liver resection.
Methods: 113 patients were included in this retrospective study: the internal training cohort comprised 66 patients, while the external validation cohort comprised 47. All patients underwent a CT study before surgery.
Int J Surg
September 2025
Department of Respiratory and Critical Care Medicine, Hubei Province Clinical Research Center for Major Respiratory Diseases, Key Laboratory of Pulmonary Diseases of National Health Commission, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
Background: Precise preoperative discrimination of invasive lung adenocarcinoma (IA) from preinvasive lesions (adenocarcinoma in situ [AIS]/minimally invasive adenocarcinoma [MIA]) and prediction of high-risk histopathological features are critical for optimizing resection strategies in early-stage lung adenocarcinoma (LUAD).
Methods: In this multicenter study, 813 LUAD patients (tumors ≤3 cm) formed the training cohort. A total of 1,709 radiomic features were extracted from the PET/CT images.
Objectives: Waterpipe smoking is increasingly becoming a public health threat due to its appealing features and misperceptions of its harmful effects. Tools assessing waterpipe addiction are essential for understanding waterpipe smokers' behaviors and designing effective smoking cessation plans. This study aimed to develop and validate the Waterpipe Addiction, Craving, and Anticipation Scale (WACAS) and describe the specific patterns and multidimensional aspects of waterpipe smoking behavior.
View Article and Find Full Text PDFCochrane Database Syst Rev
September 2025
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.
Background: Radiotherapy is the mainstay of treatment for head and neck cancer (HNC) but may induce various side effects on surrounding normal tissues. To reach an optimal balance between tumour control and toxicity prevention, normal tissue complication probability (NTCP) models have been reported to predict the risk of radiation-induced side effects in patients with HNC. However, the quality of study design, conduct, and analysis (i.
View Article and Find Full Text PDFCancer Med
September 2025
Department of Computer Engineering, Social and Biological Network Analysis Laboratory, University of Kurdistan, Sanandaj, Iran.
Background: Ovarian cancer (OC) remains the most lethal gynecological malignancy, largely due to its late-stage diagnosis and nonspecific early symptoms. Advances in biomarker identification and machine learning offer promising avenues for improving early detection and prognosis. This review evaluates the role of biomarker-driven ML models in enhancing the early detection, risk stratification, and treatment planning of OC.
View Article and Find Full Text PDF