Other Cancers

Transcriptionally informed nucleosome profiling of circulating cell-free DNA predicts breast cancer recurrence.

Cell-free DNA (cfDNA) offers a minimally invasive approach to capture genomic and epigenetic dynamics during cancer progression. We performed targeted sequencing of 26 gene loci transcriptionally regulated during the acquisition of therapy resistance in breast cancer and analyzed blood-derived cfDNA from 150 breast cancer samples (105 primary and 45 recurrent). Recurrent samples exhibited increase...

Machine Learning Model Using Pre-Cancer Therapy Cardiac Magnetic Resonance Images to Predict Cancer Therapy-Related Cardiac Dysfunction.

BACKGROUND: Predicting risk of cancer therapy-related cardiac dysfunction (CTRCD) remains challenging. OBJECTIVES: The purpose of this study was to assess if deep learning (DL) approaches using cardiac magnetic resonance (CMR) images before cancer therapy can predict subsequent CTRCD and compare them with clinical and conventional imaging models. METHODS: Women with HER2+ breast cancer receiving a...

Advances in Digital Pathology and Artificial Intelligence in the Diagnosis of Myeloid Neoplasms.

Recent advances in digital pathology and artificial intelligence (AI) are transforming our ability to diagnose myeloid neoplasms, including acute myel...

Artificial Intelligence-Powered Cystoscopy Diagnostic Support System: Clinical Application of Multiarchitecture Deep Learning Models.

PURPOSE: Cystoscopy is a crucial diagnostic tool in urology for the detection and evaluation of bladder lesions. However, its diagnostic accuracy (ACC...

Tree-based and sparse logistic models for predicting one-month postoperative performance status after surgery for spinal metastases.

PURPOSE: We aimed to develop and internally validate prediction models for one-month postoperative performance status (PS) after surgery for spinal me...

Review of systemic therapy in HCC with an approach to response assessment in clinical practice.

Systemic therapy for hepatocellular carcinoma (HCC) has undergone rapid transformation over the past decade, significantly expanding treatment options...

Predicting late radiation-associated neurocognitive and endocrine toxicity in patients with brain tumors.

PURPOSE: Neurocognitive and endocrine dysfunction are potential complications of cranial irradiation. However, risk factors are poorly understood, imp...

RAS pathway activity subtypes identified by machine learning define prognostic and immune microenvironment characteristics in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD), the predominant histological subtype of non-small cell lung cancer, remains a leading cause of cancer-related ...

Deep learning and radiomics models in patients with advanced non-small cell lung cancer treated with immunotherapy combined with stereotactic radiotherapy.

Quantitative imaging is an emerging field that may allow prediction of oncological outcomes. We investigate whether radiomics and deep learning can pr...

Machine learning-based prediction of hepatocellular carcinoma risk in steatotic liver disease: A nationwide cohort study.

BACKGROUND AND AIMS: Steatotic liver disease (SLD) has emerged as an important risk factor for hepatocellular carcinoma (HCC), often in the absence of...

Nanomedicine-based cancer immunotherapy: translational barriers, mechanistic strategies, and future perspectives.

Nanomedicine-based cancer immunotherapy integrates nanotechnology with immune modulation, representing a promising strategy to improve both the effica...

Machine-learning-model based tool for screening bone metastases from lung cancer patients in primary care practice.

PURPOSE: This study aimed to use the machine-learning methods to predict bone metastasis (BM) in patients with lung cancer. METHODS: This study includ...

Advances in immune checkpoint inhibitor therapy for microsatellite instability-high (MSI-H) and mismatch repair-deficient (dMMR) colorectal cancer: Insights from the tumor immune microenvironment.

This review systematically analyzes the relationship between the immune microenvironment characteristics of microsatellite instability-high (MSI-H) or...

Multimodal Prediction of Renal Tumor Malignancy From Radiology Reports and Structured Electronic Health Records: Retrospective Cohort Study.

BACKGROUND: Accurate preoperative prediction of renal tumor malignancy is critical for guiding decisions and reducing overtreatment, as a substantial ...

Multimodal Deep Learning for Benign vs Malignant Eyelid Lesion Classification Using Optical Coherence Tomography and Clinical Images.

PURPOSE: To evaluate the performance of deep learning models using optical coherence tomography (OCT) volumes, clinical photographs, and their multimo...

What do UK hospice websites communicate about the meaning of palliative care?

OBJECTIVES: Hospice websites are an important source of information for the public. This study examined whether information communicated about palliat...

Interpretable machine learning model using peripheral blood for non-invasive detection of moderate-to-severe myelofibrosis in JAK2 V617F-positive MPNs: A multicentre pilot proof-of-concept study.

Progression to moderate-to-severe myelofibrosis (MF) in JAK2 V617F-positive myeloproliferative neoplasms (MPNs) is often clinically silent, and bone m...

[Stratified application of CA19-9 in the surveillance of postoperative recurrence of pancreatic cancer].

Pancreatic cancer is characterized by high postoperative metastasis and recurrence rates, making the identification of early recurrence markers with h...

[MRI-based deep learning model for preoperative prediction of urothelial carcinoma with variant histology of bladder: a retrospective, multicenter study].

Objectives: To develop a deep learning model based on magnetic resonance imaging (MRI) for the preoperative prediction of urothelial carcinoma with va...

Applying artificial intelligence and machine learning framework for de novo design of pyrazole-based VEGFR-2 inhibitors.

VEGFR-2 is an important target for oncological interventions due to its key role in angiogenesis, a biological process vital for tumour expansion and ...