Oncology/Hematology

A multi-paradigm evaluation spanning pixels to voxels for deep learning-based kidney tumor segmentation.

Automated segmentation of kidney tumors from computed tomography (CT) scans is crit- ical for diagnosis, treatment planning, and monitoring of renal cell carcinoma (RCC). While recent deep learning models report high Dice scores (>0.97), their clinical utility remains questionable due to false positive predictions that misclassify healthy tissue as tumors and computational constraints limiting rea...

A Preliminary Study of a Machine Learning Prediction of Poorly Differentiated Hepatocellular Carcinoma Based on a Comprehensive Parameter Analysis Using Dual-Energy Computed Tomography.

OBJECTIVE: To develop and evaluate the performance of a predictive machine learning model for poorly differentiated hepatocellular carcinoma (p-HCC) using comprehensive quantitative parameters from dual-energy computed tomography (DECT). MATERIALS AND METHODS: We retrospectively analyzed 181 surgically resected, pathologically proven HCCs in 170 patients who had undergone preoperative DECT between...

HP-DIL: Deep heterogeneity profiling with graph-informed disentangled interaction learning for MRI-based liver fibrosis staging.

Liver fibrosis staging (LFS) informs treatment decisions and prognostic assessment in liver disease. Multiparametric MRI enables non-invasive, quantit...

Augmenting Large Language Model With Prompt Engineering and Supervised Fine-Tuning in Non-Small Cell Lung Cancer Tumor-Node-Metastasis Staging: Framework Development and Validation.

BACKGROUND: Accurate tumor node metastasis (TNM) staging is fundamental for treatment planning and prognosis in non-small cell lung cancer (NSCLC). Ho...

Research on Risk Transfer Pathways for Lung Cancer Among Middle-Aged and Older Individuals Using Deep Reinforcement Learning: Retrospective Cohort Study.

BACKGROUND: Nowadays, lung cancer has a significantly high incidence rate worldwide. The mortality rate of lung cancer continues to rise; it is more c...

Deep Learning-Based Contrast-Enhanced Ultrasound for Ki-67 Assessment and Prognosis in Hepatocellular Carcinoma.

Ki-67 is a critical prognostic marker for hepatocellular carcinoma (HCC), yet its clinical assessment relies on invasive biopsy. This study aimed to d...

Brain tumors classification using electrical bioimpedance spectroscopy based on a multi-scale feature extraction network with frequency band attention mechanism.

Electrical bioimpedance (EBI) measurement provides insights into the biophysical properties of tissues, offering valuable information for tumor diagno...

[177Lu]Lu-PSMA extravasation: from quantitative imaging to clinical guidelines.

Extravasation of therapeutic radioligands such as [177Lu]Lu-PSMA-617 or [177Lu]Lu-DOTATATE is rare but may result in localized radiation injury. In th...

AI triage of duodenal biopsies improves workflow.

AIMS: To develop, deploy and evaluate artificial intelligence (AI) for triaging duodenal biopsies within a National Health Service (NHS) histopatholog...

A deep learning-based digital biopsy for predicting early recurrence in gastric cancer.

Early postoperative recurrence is a major cause of treatment failure in patients with locally advanced gastric cancer (LAGC), yet current staging syst...

Decoding immunotherapy response through computational modeling.

Immunotherapy has seen success in treating patients with cancer, but variable responses underscore the need for effective patient stratification and t...

FT-MDNNMDs: early detection of breast cancer using fine-tuned multi-deep neural networks with TCGA and clinical image datasets.

Breast cancer remains one of the leading causes of cancer-related mortality among women worldwide. Early and accurate detection is critical for improv...

AI-Generated Clinical Images of Head-and-Neck Lesions in Plastic Surgery Education: An Expert Evaluation.

BACKGROUND: Clinical images are essential in plastic and reconstructive surgery education, particularly for understanding pathology, planning reconstr...

Haploidentical versus matched unrelated donor transplantation with post-transplant cyclophosphamide: a platform-dependent machine learning analysis of donor age.

In allogeneic hematopoietic cell transplantation with post-transplant cyclophosphamide (PTCy), clinicians frequently face a critical choice between a ...

Early detection of oral squamous cell carcinoma using five tumor-associated autoantibodies and a Naive Bayes-based machine learning model.

Malignant Cerebral Edema after Large-Core Anterior Circulation Stroke in the Thrombectomy Era: Prediction and Neurocritical Care Pathways.

Large-core anterior circulation ischemic stroke (LCIS) complicated by malignant cerebral edema (MCE) remains a leading cause of early death and profou...

Convergence of multiplexed immunosensors, nanotechnology, and AI for early pancreatic cancer diagnosis.

Pancreatic cancer (PC) remains one of the deadliest malignancies, largely because of its asymptomatic onset, rapid progression, and absence of sensiti...

An intelligent fusion model for Ki-67 prediction in non-small cell lung cancer: A cloud-based prediction system integrating radiomics.

BACKGROUND: The expression level of Ki-67 affects the prognosis of NSCLC patients. OBJECTIVE: Accurate preoperative prediction of Ki-67 expression in ...

Multi-site validation of an AI-based biomarker test for determining ER, PR, and HER2 status from H&E-stained breast cancer slides.

BACKGROUND: The assessment of estrogen/progesterone receptors (ER/PR) and human epidermal growth factor receptor 2 (HER2) is essential for managing br...

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 ...