Other Cancers

Classifying Stereotactic Radiosurgery Patients by Primary Diagnosis Using Natural Language Processing of Clinical Notes.

PURPOSE: Accurate identification of the primary tumor diagnosis of patients who have undergone stereotactic radiosurgery (SRS) from electronic health records is a critical but challenging task. Traditional methods of identifying the primary tumor histology relying on International Classification of Diseases (ICD)9 and ICD10 CM codes often fall short in granularity and completeness, particularly fo...

Integrating Machine Learning Algorithms to Construct a Triaptosis-Related Prognostic Model in Melanoma.

INTRODUCTION: Melanoma is a highly aggressive skin cancer that accounts for a disproportionate number of skin cancer-related deaths due to early metastasis and therapy resistance. Programmed cell death (PCD), including ferroptosis and apoptosis, plays a crucial role in tumor progression and therapy response. Among these, triaptosis is a newly described form of PCD. It represents a novel mechanism ...

Radiogenomic correlation of hypoxia-related biomarkers in clear cell renal cell carcinoma.

PURPOSE: This study aimed to evaluate radiomic models' ability to predict hypoxia-related biomarker expression in clear cell renal cell carcinoma (ccR...

High visceral-to-subcutaneous fat area ratio is an unfavorable prognostic indicator in patients with uterine sarcoma.

PURPOSE: Uterine sarcoma is a rare disease whose association with body composition parameters is poorly understood. This study explored the impact of ...

Artificial intelligence-based quantitative bone marrow pathology analysis for myeloproliferative neoplasms.

The evaluation of bone marrow pathology is essential for diagnosing and classifying myeloproliferative neoplasms (MPNs). However, morphological assess...

Development of Machine Learning Models to Predict Tumor Endoprosthesis Survival.

BACKGROUND AND OBJECTIVES: Endoprosthetic reconstruction is the preferred approach for limb salvage surgery for many patients following malignant bone...

Integrating transcriptomics and hybrid machine learning enables high-accuracy diagnostic modeling for nasopharyngeal carcinoma.

BACKGROUND: Nasopharyngeal carcinoma (NPC) lacks biomarkers demonstrating both high specificity and sensitivity for early diagnosis. This study aimed ...

Clinical decision tree for optimising endoscopic assessment of signet ring cell carcinoma in hereditary diffuse gastric cancer surveillance.

Background and study aims Prophylactic total gastrectomy (PTG) is the definitive treatment for hereditary diffuse gastric cancer syndrome (HDGC). Endo...

Preirradiation of Spheroids with Ac-Trastuzumab Improves Penetration of Ac-Liposomes and MIRDcell Predictions of Responses to Drug Cocktails.

This investigation examined the factors involved in predicting the responses of micrometastases to targeted Ac-based therapies and in optimizing these...

Multi-omics integration of TPX2 in prognostic prediction in resectable hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a malignant tumor with high incidence and mortality rates globally, significantly affecting patient prognosis and qu...

AI-Supported Documentation and Clinical Monitoring in Palliative Care: A Real-World Observational Study.

BackgroundPatients in palliative care often experience prolonged hospital stays, requiring detailed documentation, complex symptom management, and mul...

Analysis and characterization of extrachromosomal circular DNA in prostate cancer: Potential biomarker discovery from urine, plasma, and tumor samples.

Extrachromosomal circular DNA (eccDNA) may contribute to genomic rearrangements and tumor heterogeneity, playing a role in cancer development and prog...

Pretreatment Multi-sequence Contrast-Enhanced MRI to Predict Response to Immunotherapy in Unresectable Hepatocellular Carcinoma Using Transformer: A Multicenter Study.

Targeted combined immunotherapy (TCI) has shown certain antitumor effects in patients with unresectable hepatocellular carcinoma(uHCC), but only a su...

Integrated machine learning based on cuproptosis and RNA methylation regulators to explore the molecular model of prostate cancer and provide novel insights to immunotherapy.

As a highly prevalent tumor in males, prostate cancer (PCa) needs newly developed biomarkers to guide prognosis and treatment. However, few researche...

Integrative multi-omics profiling deciphers tumor microenvironment heterogeneity and immunotherapy vulnerabilities in lung neuroendocrine carcinomas.

INTRODUCTION: Lung neuroendocrine carcinomas (Lu-NECs) are rare, highly aggressive lung tumors with poor prognosis and limited therapeutic options. Un...

Time-Gated Raman Spectroscopy Combined with Deep Learning for Rapid, Label-Free Histopathological Discrimination of Gastric Cancer.

Gastric cancer is one of the most common malignant tumors of the digestive system, with a high mortality rate due to late-stage diagnosis. Current cli...

Next-Generation Sequencing-Based Testing Among Patients With Advanced or Metastatic Nonsquamous Non-Small Cell Lung Cancer in the United States: Predictive Modeling Using Machine Learning Methods.

BACKGROUND: Next-generation sequencing (NGS) has become a cornerstone of treatment for lung cancer and is recommended in current treatment guidelines ...

Extremity Soft Tissue Sarcoma Reconstruction Nomograms: A Clinicoradiomic, Machine Learning-Powered Predictor of Postoperative Outcomes.

PURPOSE: The choice of wound closure modality after limb-sparing extremity soft-tissue sarcoma (eSTS) resection is fraught with uncertainty. Leveragin...

Effects of concurrent HER2-directed therapy on development of cerebral radionecrosis after stereotactic radiotherapy: a systematic review.

PURPOSE: With increasing use of human epithelial growth factor receptor two (HER2)-targeted therapies, outcomes for numerous breast cancer patients ha...

Use of natural language processing to identify inflammatory breast cancer cases across a healthcare system.

Early identification and referral of inflammatory breast cancer (IBC) remains challenging within large healthcare systems, limiting access to speciali...