Latest AI and machine learning research in breast cancer for healthcare professionals.
Objective: Tumor-infiltrating lymphocytes (TILs) in breast cancer are one of the most important indicators of the immune response within the tumor microenvironment. They play a particularly significant prognostic and predictive role in triple-negative and HER2-positive subtypes. However, substantial inter-observer variability has been reported in TIL scoring among pathologists, which limits its re...
Objective Accurate prognostication of recurrence risk in HR+/HER2- early breast cancer is central for therapeutic decision-making, including identifying patients who may safely avoid adjuvant systemic therapy. However, the performance of existing prognostic tools remains insufficient for effective clinical stratification, motivating the development of artificial intelligence (AI)-based methods to ...
Cancer is a disease of the genome, in which somatic mutations and copy-number alterations determine tumour identity, clinical behaviour, and response ...
Background: CD8+ tumor-infiltrating lymphocytes (TILs) are established prognostic markers in colorectal cancer, yet the clinical significance of CD103...
Background Background breast features are frequently noted in pathology reports alongside invasive breast cancer but rarely factor into prognosis or t...
Background: African Americans (AA) experience disproportionate burden of colorectal cancer (CRC). Dysregulation of the Wingless-related integration si...
Treatment of advanced head and neck squamous cell carcinoma (HNSCC) often involves radiotherapy combined with chemotherapy, targeted therapy, or immun...
Ionizing radiation induces molecular responses that may be used to estimate exposure when physical dosimeters are unavailable. Here we present two lar...
Whether individual transcripts carry intrinsic features that predetermine their response to external perturbations is unknown. Here we used nanopore d...
Ovarian cancer is the most lethal gynecologic malignancy: around 60% of patients are diagnosed at an advanced stage, with an associated 5-year surviva...
Current treatment of IDH-wildtype glioblastoma (GBM) relies on the first-line chemotherapy-temozolomide. Although MGMT methylation is routinely conduc...
Accurate classification of breast cancer subtypes from gene expression data is critical for diagnosis and treatment selection. However, such datasets ...
We introduce a new strategy for compositional neural surrogates for radiation-matter interactions, a key task spanning domains from particle physics t...
Predicting the anatomical site of metastasis from a primary tumour remains an unsolved problem in breast cancer (BRCA) and metastatic disease more bro...
Background: Triple-negative breast cancer (TNBC) exhibits substantial molecular heterogeneity and lacks targeted receptor therapies. Single-omic appro...
Mechanistic modeling has long been used as a tool to describe the dynamics of biological systems, especially cancer in response to treatment. Their ke...
Chemotherapy dose optimization can be formulated as a dynamic treatment regime, requiring sequential decisions under uncertainty that must balance tum...
Accurate histological differentiation between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) is critical for personalized treatment in non-sma...
Gastric cancer patients frequently experience skeletal muscle loss during the perioperative and adjuvant treatment period, which has been associated w...
Motivation: Multi-omics integration can improve cancer subtyping, but modality informativeness and noise vary across cancer types and patients. Existi...