Oncology/Hematology

Challenges and Opportunities for Global Cervical Cancer Elimination: How Can We Build a Model for Other Cancers?

Cervical cancer remains a leading cause of cancer-related death among women globally, despite the av...

Improving lung cancer diagnosis and survival prediction with deep learning and CT imaging.

Lung cancer is a major cause of cancer-related deaths, and early diagnosis and treatment are crucial...

Monitoring of Early Skin Reactions by Optical Coherence Tomography and Dermatoscopy in Patients Receiving Radiation Therapy for Head and Neck Cancer.

PURPOSE: Patients with head and neck cancer undergoing radiation therapy (RT) may experience pronoun...

Deep learning and inflammatory markers predict early response to immunotherapy in unresectable NSCLC: A multicenter study.

Immune checkpoint inhibitors (ICIs) demonstrate substantial interpatient variability in clinical eff...

Challenges and Advances in Classifying Brain Tumors: An Overview of Machine, Deep Learning, and Hybrid Approaches with Future Perspectives in Medical Imaging.

Accurate brain tumor classification is essential in neuro-oncology, as it directly informs treatment...

Thalamic neural activity and epileptic network analysis using stereoelectroencephalography: a prospective study protocol.

INTRODUCTION: Epilepsy is a prevalent chronic neurological disorder, with approximately one-third of...

Preoperative prediction model for benign and malignant gallbladder polyps on the basis of machine-learning algorithms.

BACKGROUND: This study aimed to differentiate between benign and malignant gallbladder polyps preope...

"Artificial intelligence and multi-modal data integration in renal cell carcinoma a review of its potential and limitations".

UMAP-based clustering split for rigorous evaluation of AI models for virtual screening on cancer cell lines.

Virtual Screening (VS) of large compound libraries using Artificial Intelligence (AI) models is a hi...

Empirical evaluation of artificial intelligence distillation techniques for ascertaining cancer outcomes from electronic health records.

Phenotypic information for cancer research is embedded in unstructured electronic health records (EH...

Predicting atezolizumab response in metastatic urothelial carcinoma patients using machine learning on integrated tumour gene expression and clinical data.

Atezolizumab is a treatment for metastatic urothelial carcinoma (mUC), yet only 23% of mUC patients ...

Use of natural language processing to identify inflammatory breast cancer cases across a healthcare system.

Early identification and referral of inflammatory breast cancer (IBC) remains challenging within lar...

IoT-Driven Skin Cancer Detection: Active Learning and Hyperparameter Optimization for Enhanced Accuracy.

Skin cancer, one of the most prevalent and lethal cancer types, poses significant challenges for ear...

Molecular biomarkers for the prognosis of breast cancer: role of amino acid metabolism genes.

The development of precise molecular biomarkers for breast cancer prognosis holds immense potential ...

Effects of concurrent HER2-directed therapy on development of cerebral radionecrosis after stereotactic radiotherapy: a systematic review.

PURPOSE: With increasing use of human epithelial growth factor receptor two (HER2)-targeted therapie...

Intraoperative hypotension during robotic-assisted radical prostatectomy: A randomised controlled trial comparing standard goal-directed fluid therapy with hypotension prediction index-guided goal-directed fluid therapy.

BACKGROUND: Robot-assisted radical prostatectomy (RARP) represents the leading application of roboti...

Label-free diagnosis of lung cancer by Fourier transform infrared microspectroscopy coupled with domain adversarial learning.

Lung cancer is one of the most prevalent malignancies, characterized by high morbidity and mortality...

Explainable machine learning model for predicting internal mammary node metastasis in breast cancer: Multi-method development and cross-cohort validation.

BACKGROUND: This study developed an explainable machine learning model for baseline internal mammary...

Identification of DSC2 as a Key Biomarker for Induction Chemotherapy Sensitivity in Locally Advanced Laryngeal and Hypopharyngeal Squamous Cell Carcinoma.

Patients with locally advanced laryngeal and hypopharyngeal squamous cell carcinoma (LA-LHSCC) urgen...

Integrated muti-omics data and machine learning reveal CD151 as a key biomarker inducing chemoresistance in metabolic syndrome-related early-onset left-sided colorectal cancer.

Emerging evidence has suggested a potential pathological association between early-onset left-sided ...

Deep Learning in Digital Breast Tomosynthesis: Current Status, Challenges, and Future Trends.

The high-resolution three-dimensional (3D) images generated with digital breast tomosynthesis (DBT) ...