Other Cancers

Comparative 10-year performance of mammography artificial intelligence, polygenic, and clinical breast cancer risk models in the Kaiser Permanente Research Bank.

BACKGROUND: We compared performance across 3 breast cancer risk domains-clinical, polygenic, and mammography artificial intelligence-alone and in combination over a 10-year time horizon among women with a negative screening mammogram within a Kaiser Permanente Research Bank (KPRB) prospective cohort. METHODS: The study included 82 957 women (61 962 non-Hispanic White, 7256 Asian, 3414 Black, and 5...

Mechanobiology of the tumor microenvironment: a review of therapeutic interactions and in vitro elasticity measurement techniques.

The stiffness of the extracellular matrix (ECM) regulates cellular behavior, influencing tumor progression and therapeutic resistance. In cancer, aberrant ECM stiffening can reduce immune cell infiltration and treatment efficacy, which can in turn alter the tumor microenvironment. Here, we review the role of ECM stiffness in cancer biology and its relevance to matrix-targeted therapies and biomate...

Development and validation of a machine learning-based postoperative staging system for hilar cholangiocarcinoma: a retrospective single-center cohort study.

BACKGROUND: Hilar cholangiocarcinoma (HCCA) is a malignant tumor at the hepatic hilum with poor prognosis and survival despite surgical resection. Whi...

Integrating neurobiological markers to prospectively predict adolescent non-suicidal self-injury and suicide attempts: a machine learning approach.

BACKGROUND: Suicide attempts (SA) and non-suicidal self-injury (NSSI) are closely related phenomena, both common in adolescent clinical samples. This ...

Single-cell RNA sequencing in ovarian cancer: decoding the tumor microenvironment for personalized therapy.

Ovarian cancer (OC) remains a leading cause of mortality among gynecological malignancies, largely due to profound inter- and intra-tumoral heterogene...

A highly interpretable machine learning model for predicting lung cancer bone metastasis: uncovering the synergistic effect of routine biochemical markers.

BACKGROUND: Bone metastasis (BM) significantly impairs lung cancer prognosis and patient quality of life. Conventional imaging modalities often face l...

Leveraging Large Language Models to Integrate Clinical Knowledge and Machine Learning Predictions for Lymph Node Metastasis Prediction: Development of a Knowledge-Augmented Framework.

BACKGROUND: Lymph node metastasis (LNM) is a critical clinical indicator for determining the initial treatment strategy for patients with lung cancer....

An innovative deep learning paradigm for automated detection and accurate classification of lung nodules in magnetic resonance imaging.

Lung cancer, the predominant kind of cancer, needs considerable care, since inadequate treatment may lead to fatal outcomes. The integration of comput...

Integrative single-cell and bulk transcriptomics reveal cuproptosis subtypes, prognostic models, and COL5A1 as a key gene in glioblastoma.

Glioblastoma (GBM) remains one of the most aggressive primary brain tumors with limited therapeutic options. Cuproptosis, a recently identified copper...

Predicting Renal Tumor Pathology from Intraoperative Gross Appearance: An AI-Based Pilot Study.

OBJECTIVE: To evaluate the feasibility of using convolutional neural networks (CNNs) and vision transformers (ViTs) to predict renal tumor pathology i...

Effects of breast cancer risk factors on the tumor microenvironment: a morphological deep-learning analysis of three prospective cohorts.

Emerging evidence suggests a critical role of the tumor microenvironment (TME) in breast cancer (BC) development and outcomes, yet factors that modify...

An intelligent MRI-based all-in-one diagnostic strategy for axillary lymph node status in breast cancer.

An integrated diagnostic strategy of preoperative identification of sentinel lymph node (SLN) metastasis, SLN metastatic burden, and non-SLN (NSLN) me...

PD-YOLO: a high-precision detection network for fine-grained lung cancer and multi-scale pulmonary nodules in CT images.

Timely and accurate Computed Tomography (CT) screening is crucial for the early clinical treatment of lung cancer and preventing the progression of ma...

Deep learning-enabled single-cell morpholomic atlas of nasal swabs distinguishes chronic inflammation from sinonasal malignancy.

Sinonasal malignancies frequently present with symptoms overlapping chronic inflammatory conditions, complicating early detection and delaying treatme...

A Computationally Efficient and Improved Brain Tumor Recognition System by MRI-Segmentation Integrated Classification Network.

Brain tumors present a major global health concern, and a precise diagnosis is essential for proper treatment. Many existing MRI-based machine learnin...

A bibliometric analysis of artificial intelligence in ovarian cancer research from 2006 to 2025.

BACKGROUND: Ovarian cancer is a gynecological malignancy associated with high mortality and poses significant clinical challenges in early diagnosis a...

Transcriptomic identification of key genes influencing m7G modification in thyroid carcinoma and experimental validation.

BACKGROUND: N7-methylguanosine (m7G) modification plays a critical role in RNA metabolism and is increasingly recognized for its implications in cance...

Scenario-based multi-parametric QC for quality control of complex algorithms used in clinical care.

Complex algorithms and prediction models are increasingly being developed, investigated and applied for clinical use in medical laboratories and beyon...

Expression of the High Affinity Neurotensin Receptor Defines an Immune‑cold, Poor‑prognosis Colorectal Cancer Subtype.

OBJECTIVE: We investigated neurotensin receptor 1 (NTSR1) as a potential mediator of the mechanical immune barrier that contributes to T-cell exclusio...

MTA-Swin: A Multi-Token Attention Swin Transformer for Brain Tumor Classification with Leakage-Free MRI Benchmarking.

Brain tumors represent a major global health challenge, and accurate classification of brain tumors is essential for effective diagnosis and treatment...