Latest AI and machine learning research in oncology/hematology for healthcare professionals.
BACKGROUND: To develop a combined model integrating intratumoral and peritumoral delta-radiomics from multi-parametric MRI with clinical features for predicting pathological complete response (pCR, i.e., Miller-Payne grade V response) to neoadjuvant chemotherapy (NAT) in breast cancer. METHODS: A total of 254 patients with breast cancer from two hospitals were retrospectively included. Radiomics f...
BACKGROUND: Accurate identification of patients at high risk of pulmonary infection after thoracoscopic lung cancer resection is important for timely and targeted preventive measures. Methods for determining the risk of pulmonary infection after thoracoscopic lung cancer resection have not been well studied. METHODS: This study was a retrospective case-control research project. The information of ...
BACKGROUND: Neoantigens-tumor-specific peptides generated by somatic mutations-are central targets of effective anticancer T cell immunity and underpi...
Spatial transcriptomics enables the systematic exploration of how gene expression patterns are organized within intact tissues, yet effective analysis...
BACKGROUND: Colorectal cancer (CRC) is characterized by genetic variation, epigenetic alterations, microenvironmental imbalance, and metabolic reprogr...
Human epidermal growth factor receptor 2 (HER2)-targeted therapies have revolutionized breast cancer treatment, necessitating standardized HER2 testin...
The efficient capture and sensitive detection of exosomes from complex biological samples remain critical challenges for liquid biopsy-based cancer di...
Sialylated alpha-fetoprotein (sAFP) is a very potential marker for the pathogenesis exploration and clinical assessment of hepatocellular carcinoma (H...
Tumor vasculature has traditionally been viewed as structurally and functionally abnormal and, therefore, is primarily targeted for inhibition. Howeve...
BACKGROUND: The clinical relevance of concordance between multidisciplinary tumor board (MDT) decisions and artificial intelligence (AI)-based treatme...
INTRODUCTION: The management of rectal adenocarcinoma requires navigation of complex, branching guideline pathways encompassing neoadjuvant sequencing...
Brain tumors remain among the most lethal cancers, largely due to their remarkable heterogeneity, plasticity, and resistance to therapy. The second Br...
BACKGROUND: Colorectal cancer (CRC) exhibits pronounced biological diversity, a feature increasingly attributed to alterations in cellular metabolic r...
BACKGROUNDS: Breast cancer (BRCA) represents the most prevalent malignancy globally, with projections indicating 3.2 million new cases anticipated by ...
BACKGROUND: Diffuse gliomas remain among the most surgically challenging tumors, characterized by their infiltrative nature, proximity to eloquent bra...
Medically specialized AI systems that have obtained regulatory clearance as medical devices can be deployed for patient-specific clinical decision sup...
BACKGROUND: Colorectal cancer (CRC) is a prevalent malignant tumor with increasing incidence and mortality rates worldwide. Exosomes are secretory ves...
BACKGROUND: Doxorubicin (DOX)-based chemotherapy has improved survival outcomes in breast cancer patients but is often limited by doxorubicin-induced ...
BACKGROUND: Hepatocellular carcinoma (HCC) is a highly lethal malignancy with poor prognosis, and effective biomarkers for predicting immunotherapy re...
BACKGROUND: Hepatocellular carcinoma (LIHC) features a complex tumor microenvironment (TME) where tumor-associated neutrophils (TANs) show significant...