Other Cancers

Artificial intelligence for the prediction of synchronous and metachronous liver metastasis in colorectal cancer patients: a systematic review and meta-analysis.

BACKGROUND: Colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer mortality in the world. Liver is the most common metastasis site (synchronous and metachronous) in this cancer, affecting 12.8% of these patients. Artificial intelligence (AI) models have shown significant potential in aiding the diagnosis of CRLM. Radiomic models extract quantitative feature...

Research on Lung Cancer Classification Based on Multidimensional Hematological Indicators and Machine Learning Models.

Accurate subtyping of lung cancer is crucial for developing personalized treatment plans and improving patient outcomes. This study established machine learning models for lung cancer subtyping by integrating multidimensional hematological indicators, offering advantages such as non-invasiveness, repeatability, and the capability for dynamic disease monitoring. The study utilized data from 771 lun...

Tumor cell villages define the co-dependency of tumor and microenvironment in liver cancer.

Spatial cellular context is crucial in shaping intratumor heterogeneity. However, understanding how each tumor establishes its unique spatial landscap...

A comparative analysis of data-driven models for breast cancer survival prediction.

Breast cancer is the most frequently diagnosed cancer among women and persists as a societal problem worldwide. It remains a leading cause of cancer a...

Lactate metabolism-driven tumor heterogeneity and molecular signatures in intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) is a highly aggressive liver malignancy with limited therapeutic options and poor prognosis. Recent ...

Emerging trends and converging evidence in tumor evolution: A comprehensive review.

BACKGROUND: Tumor evolution is a spatiotemporal dynamic process orchestrated by the interplay of genetic mutations, epigenetic reprogramming, and bidi...

A perturbed multilayer perceptron approach to predicting distant metastatic sites of cancer patients.

Cancer metastasis accounts for about 90% of cancer-related mortality, but is difficult to predict. In particular, distant metastasis is more difficult...

Artificial Intelligence Impact on Radiologist Performance in Breast Cancer Screening with Digital Breast Tomosynthesis.

PURPOSE: Assess impact of artificial intelligence (AI) on radiologists' detection of cancer on digital breast tomosynthesis (DBT) exams based on densi...

Immunotherapy in Triple-Negative Breast Cancer: From Molecular Mechanisms to Precision Medicine-Overcoming Resistance and Optimizing Clinical Outcomes.

Triple-negative breast cancer (TNBC) is the most violent type of breast cancer, in which estrogen receptors (ER), progesterone receptors (PR), and hum...

Interpretable Ensemble Machine Learning Prediction of Nonadherence and the Risk of Nonpersistence of Targeted Disease-Modifying Antirheumatic Agents in Older Adults With Rheumatoid Arthritis.

PURPOSE: Ensemble machine learning (ML) demonstrated potential for improving predictions based on big health care data. We developed and validated int...

Distinction Between Benign and Borderline/Malignant Phyllodes Tumor in Breast Mammography and Ultrasound Based on Radiomics Methods.

RATIONALE AND OBJECTIVES: This study aims to evaluate whether radiomics methods used on breast mammography (MG) and ultrasound (US) could distinguish ...

Multiparametric MRI-Based Deep Learning and Radiomics for Predicting Progression-Free Survival Benefit in Patients with Hepatocellular Carcinoma Treated with Immunotherapy and Targeted Therapy Plus Transarterial Chemoembolization: A Bicentric Study.

RATIONALE AND OBJECTIVES: The non-invasive biomarkers for predicting progression-free survival (PFS) in patients with hepatocellular carcinoma (HCC) t...

Single-cell transcriptomic analysis and machine learning identify ATAD3A as a key gene that stabilizes mitochondrial-endoplasmic reticulum membranes, promoting bladder cancer progression.

BACKGROUND: Mitochondria-associated endoplasmic reticulum membranes (MAM) play a critical regulatory role in cancer, yet their function in bladder can...

Artificial intelligence differentiates prefibrotic primary myelofibrosis with thrombocytosis from essential thrombocythemia using digitized bone marrow biopsy images.

Prefibrotic primary myelofibrosis (prePMF) and essential thrombocythemia (ET) are distinct myeloproliferative neoplasms (MPNs) with overlapping clinic...

Multimodal ultrasound and artificial intelligence for characterization of thyroid nodules in Hashimoto's thyroiditis: current challenges and future perspectives.

Patients with Hashimoto's thyroiditis (HT) frequently present with concurrent nodular lesions such as nodular goiter and thyroid cancer (especially pa...

Machine Learning Prediction of Recurrence in Pediatric Thyroid Cancer: Malignant Endocrine Tumors Cohort Analysis Using XGBoost and SHAP.

CONTEXT: Pediatric differentiated thyroid carcinoma (DTC) often presents with advanced disease but generally has excellent long-term survival. However...

Machine learning based classification of aggressive and malignant renal tumors from multimodal data.

This study aimed to develop and evaluate a machine learning pipeline using multiphase contrast-enhanced CT images and clinical data to classify renal ...

Biomarkers and advances in AML-MRC: from bench to bedside.

Acute myeloid leukemia with myelodysplasia-related changes (AML-MRC) represents a high-risk subtype of AML, characterized by poor prognosis and limite...

The optimal conditioning intensity of stem cell transplantation for acute myeloid leukemia in complete remission.

UNLABELLED: This study aimed to identify patient groups in which myeloablative conditioning (MAC) or reduced-intensity conditioning (RIC) regimens ind...

Dual-Stream Deep Feature and Cell Phenotype Fusion Model for the Diagnosis of Myeloproliferative Neoplasms.

Diagnosing myeloproliferative neoplasms (MPNs) is challenging due to the nuanced and overlapping clinical manifestations of the various subtypes. Prec...