Oncology/Hematology

Smart nanomedicines powered by artificial intelligence: a breakthrough in lung cancer diagnosis and treatment.

Lung cancer remains one of the leading causes of cancer-related mortality worldwide, primarily due t...

Circular RNAs: driving forces behind chemoresistance and immune evasion in bladder cancer.

Bladder cancer (BCa) is characterized by recurring relapses and the emergence of chemoresistance, es...

Predictive power of artificial intelligence for malignant cerebral edema in stroke patients: a CT-based systematic review and meta-analysis of prevalence and diagnostic performance.

Malignant cerebral edema (MCE) is a severe complication of acute ischemic stroke, with high mortalit...

Machine learning based radiomics approach for outcome prediction of meningioma - a systematic review.

INTRODUCTION: Meningioma is the most common brain tumor in adults. Magnetic resonance imaging (MRI) ...

Prediction model of gastrointestinal tumor malignancy based on coagulation indicators such as TEG and neural networks.

OBJECTIVES: Accurate determination of gastrointestinal tumor malignancy is a crucial focus of clinic...

Optimizing skin cancer screening with convolutional neural networks in smart healthcare systems.

Skin cancer is among the most prevalent types of malignancy all over the global and is strongly asso...

"Artificial Intelligence in NAFLD Diagnosis: A New Frontier in Managing Metastatic Prostate Cancer Risk".

Optimizing imaging modalities for sarcoma subtypes in radiation therapy: State of the art.

The choice of imaging modalities is essential in sarcoma management, as different techniques provide...

Foundation Model and Radiomics-Based Quantitative Characterization of Perirenal Fat in Renal Cell Carcinoma Surgery.

RATIONALE AND OBJECTIVES: To quantitatively characterize the degree of perirenal fat adhesion using ...

Early-stage lung cancer detection via thin-section low-dose CT reconstruction combined with AI in non-high risk populations: a large-scale real-world retrospective cohort study.

BACKGROUND: Current lung cancer screening guidelines recommend annual low-dose computed tomography (...

Establishment of a deep-learning-assisted recurrent nasopharyngeal carcinoma detecting simultaneous tactic (DARNDEST) with high cost-effectiveness based on magnetic resonance images: a multicenter study in an endemic area.

BACKGROUND: To investigate the feasibility of detecting local recurrent nasopharyngeal carcinoma (rN...

Precision Oncology in Non-small Cell Lung Cancer: A Comparative Study of Contextualized ChatGPT Models.

OBJECTIVES: The growing adoption of Large Language Models (LLMs) in medicine has raised important qu...

A tumor-infiltrating B lymphocytes -related index based on machine-learning predicts prognosis and immunotherapy response in lung adenocarcinoma.

INTRODUCTION: Tumor-infiltrating B lymphocytes (TILBs) play a pivotal role in shaping the immune mic...

Brain tumor intelligent diagnosis based on Auto-Encoder and U-Net feature extraction.

Preoperative classification of brain tumors is critical to developing personalized treatment plans, ...

Deciphering the molecular fingerprint of haemoglobin in lung cancer: A new strategy for early diagnosis using two-trace two-dimensional correlation near infrared spectroscopy (2T2D-NIRS) and machine learning techniques.

Lung cancer remains one of the deadliest malignancies worldwide, highlighting the need for highly se...

Artificial intelligence-assisted magnetic resonance lymphography for evaluation of micro- and macro-sentinel lymph node metastasis in breast cancer.

Contrast-enhanced magnetic resonance lymphography (CE-MRL) plays a crucial role in preoperative diag...

Liver Tumor Prediction using Attention-Guided Convolutional Neural Networks and Genomic Feature Analysis.

The task of predicting liver tumors is critical as part of medical image analysis and genomics area ...

Evaluating the prognostic significance of artificial intelligence-delineated gross tumor volume and prostate volume measurements for prostate radiotherapy.

BACKGROUND AND PURPOSE: Artificial intelligence (AI) may extract prognostic information from MRI for...

Pan-cancer analysis of CDC7 in human tumors: Integrative multi-omics insights and discovery of novel marine-based inhibitors through machine learning and computational approaches.

Cancer remains a significant global health challenge, with the Cell Division Cycle 7 (CDC7) protein ...

Deep learning informed multimodal fusion of radiology and pathology to predict outcomes in HPV-associated oropharyngeal squamous cell carcinoma.

BACKGROUND: We aim to predict outcomes of human papillomavirus (HPV)-associated oropharyngeal squamo...

Deep learning-based analysis of gross features for ovarian epithelial tumors classification: A tool to assist pathologists for frozen section sampling.

Computational pathology has primarily focused on analyzing tissue slides, neglecting the valuable in...