AIMC Topic: Biomarkers, Tumor
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Multimodal deep learning for predicting PD-L1 biomarker and clinical immunotherapy outcomes of esophageal cancer.
Frontiers in immunology
Mar 11, 2025
Although the immune checkpoint inhibitors (ICIs) have demonstrated remarkable anti-tumor efficacy in solid tumors, the proportion of ESCC patients who benefit from ICIs remains limited. Current biomarkers have assisted in identifying potential respon...
Dual-Modality Virtual Biopsy System Integrating MRI and MG for Noninvasive Predicting HER2 Status in Breast Cancer.
Academic radiology
Mar 10, 2025
RATIONALE AND OBJECTIVES: Accurate determination of human epidermal growth factor receptor 2 (HER2) expression is critical for guiding targeted therapy in breast cancer. This study aimed to develop and validate a deep learning (DL)-based decision-mak...
Nano biosensor unlocks tumor derived immune signals for the early detection of ovarian cancer.
Biosensors & bioelectronics
Mar 10, 2025
Ovarian cancer is a critical health issue for women nowadays. Its impact is significant because of its high mortality rate (324,603 worldwide), late-stage diagnosis and poor survival rate. Lack of screening tests, vague symptoms, misdiagnosis, and ag...
Enhancing pancreatic cancer diagnostics: Ensemble-based model for automated urine biomarker classification.
Computers in biology and medicine
Mar 10, 2025
This research addresses the critical challenge of early detection in pancreatic ductal adenocarcinoma (PDAC) by exploring urinary biomarkers and integrating artificial intelligence (AI) models. The study emphasizes the significance of liquid biopsy, ...
Harnessing Artificial Intelligence for Precision Diagnosis and Treatment of Triple Negative Breast Cancer.
Clinical breast cancer
Mar 8, 2025
Triple-Negative Breast Cancer (TNBC) is a highly aggressive subtype of breast cancer (BC) characterized by the absence of estrogen, progesterone, and HER2 receptors, resulting in limited therapeutic options. This article critically examines the role ...
Artificial intelligence and whole slide imaging, a new tool for the microsatellite instability prediction in colorectal cancer: Friend or foe?
Critical reviews in oncology/hematology
Mar 8, 2025
Colorectal cancer (CRC) is the third most common and second most deadly cancer worldwide. Despite advances in screening and treatment, CRC is heterogeneous and the response to therapy varies significantly, limiting personalized treatment options. Cer...
Advanced pathological subtype classification of thyroid cancer using efficientNetB0.
Diagnostic pathology
Mar 7, 2025
BACKGROUND: Thyroid cancer is a prevalent malignancy requiring accurate subtype identification for effective treatment planning and prognosis evaluation. Deep learning has emerged as a valuable tool for analyzing tumor microenvironment features and d...
Development of a MVI associated HCC prognostic model through single cell transcriptomic analysis and 101 machine learning algorithms.
Scientific reports
Mar 7, 2025
Hepatocellular carcinoma (HCC) is an exceedingly aggressive form of cancer that often carries a poor prognosis, especially when it is complicated by the presence of microvascular invasion (MVI). Identifying patients at high risk of MVI is crucial for...
Mutation
Neoplasm Invasiveness
Datasets as Topic
Liver
Microvessels
Prognosis
Kaplan-Meier Estimate
Meta-Analysis as Topic
Clinical Decision-Making
Immune Checkpoint Proteins
Immunotherapy
Biomarkers, Tumor
Humans
Gene Expression Regulation, Neoplastic
Carcinoma, Hepatocellular
Machine Learning
Risk Assessment
Treatment Outcome
Single-Cell Gene Expression Analysis
Precision Medicine
Liver Neoplasms
A deep-learning model for quantifying circulating tumour DNA from the density distribution of DNA-fragment lengths.
Nature biomedical engineering
Mar 7, 2025
The quantification of circulating tumour DNA (ctDNA) in blood enables non-invasive surveillance of cancer progression. Here we show that a deep-learning model can accurately quantify ctDNA from the density distribution of cell-free DNA-fragment lengt...
Multi-Omics Deep-Learning Prediction of Homologous Recombination Deficiency-Like Phenotype Improved Risk Stratification and Guided Therapeutic Decisions in Gynecological Cancers.
IEEE journal of biomedical and health informatics
Mar 6, 2025
Homologous recombination deficiency (HRD) is a well-recognized important biomarker in determining the clinical benefits of platinum-based chemotherapy and PARP inhibitor therapy for patients diagnosed with gynecologic cancers. Accurate prediction of ...
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