Oncology/Hematology

Manual Delineation of the Region of Interest Combined With Clinical Image Analysis to Predict the Ki-67 Expression Level in Non-small Cell Lung Cancer.

BACKGROUND: The Ki-67 antigen, a marker of cell proliferation, serves as a biomarker for assessing tumor malignancy. However, measuring Ki-67 levels through immunohistochemistry is often challenging due to difficulties in specimen collection and individual health issues. Radiological analysis has emerged as a potential alternative for predicting Ki-67 levels, although its accuracy has been limited...

Machine Learning Radiomics for Predicting Response to MR-Guided Radiotherapy in Unresectable Hepatocellular Carcinoma: A Multicenter Cohort Study.

BACKGROUND: This study was conducted to assess the efficacy and safety of magnetic resonance (MR)-guided hypofractionated radiotherapy in patients with unresectable hepatocellular carcinoma (HCC). Machine learning-based radiomics was utilized to predict responses in these patients.

A transformation uncertainty and multi-scale contrastive learning-based semi-supervised segmentation method for oral cavity-derived cancer.

OBJECTIVES: Oral cavity-derived cancer pathological images (OPI) are crucial for diagnosing oral squamous cell carcinoma (OSCC), but existing deep lea...

Single-cell and spatial transcriptomics reveal correlation between RNA methylation-related miRNA risk model and immune infiltration in hepatocellular carcinoma.

INTRODUCTION: Increasing evidence highlights the pivotal role of RNA methylation and miRNAs in hepatocellular carcinoma (HCC). However, the risk assoc...

Development of an immune-related gene signature applying Ridge method for improving immunotherapy responses and clinical outcomes in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is a major cause of cancer mortality. Considering the critical role of tumor infiltrating lymphocytes in effect...

Providing a Prostate Cancer Detection and Prevention Method With Developed Deep Learning Approach.

Prostate cancer is the second most common cancer among men worldwide. This cancer has become extremely noticeable due to the increase of prostate can...

Microbiota as diagnostic biomarkers: advancing early cancer detection and personalized therapeutic approaches through microbiome profiling.

The important function of microbiota as therapeutic modulators and diagnostic biomarkers in cancer has been shown by recent developments in microbiome...

Multi-omics analysis and experiments uncover the link between cancer intrinsic drivers, stemness, and immunotherapy in ovarian cancer with validation in a pan-cancer census.

BACKGROUND: Although immune checkpoint inhibitors (ICIs) represent a substantial breakthrough in cancer treatment, it is crucial to acknowledge that t...

Artificial intelligence-based automated breast ultrasound radiomics for breast tumor diagnosis and treatment: a narrative review.

Breast cancer (BC) is the most common malignant tumor among women worldwide, posing a substantial threat to their health and overall quality of life. ...

The value of a combined model based on ultra-radiomics and multi-modal ultrasound in the benign-malignant differentiation of C-TIRADS 4A thyroid nodules: a prospective multicenter study.

OBJECTIVE: To establish a combined model based on ultrasound radiomics combined with multimodal ultrasound and evaluate its value in diagnosing benign...

Comprehensive analysis of potential biomarkers for the diagnosis and prognosis of Cervical squamous cell carcinoma - based on GEO and TCGA databases.

BACKGROUND: Cervical squamous cell carcinoma (CESC) constitutes a substantial global health burden, especially in resource-limited regions. The identi...

Artificial intelligence and patient narratives: A novel approach to assessing hope in patients with cancer.

The present study aimed to evaluate the feasibility of patient-generated text and its interpretation by artificial intelligence (AI) as a valid correl...

Pyroptosis-Related Gene Signatures Enable Robustly Diagnosis, Prognosis and Immune Responses Prediction in Uterine Corpus Endometrial Carcinoma.

Uterine corpus endometrial carcinoma (UCEC) is a gynecological malignancy with poor prognosis and high lethality rates. Pyroptosis, a pro-inflammator...

RRFNet: A free-anchor brain tumor detection and classification network based on reparameterization technology.

Advancements in medical imaging technology have facilitated the acquisition of high-quality brain images through computed tomography (CT) or magnetic ...

Cytopathological quantification of NORs using artificial intelligence to oral cancer screening.

Oral squamous cell carcinoma (OSCC) remains the most prevalent neoplasm of the head and neck. In recent decades, the incidence and prevalence of OSCC ...

Autoencoder techniques for survival analysis on renal cell carcinoma.

Survival is the gold standard in oncology when determining the real impact of therapies in patients outcome. Thus, identifying molecular predictors of...

Personalized treatment decision-making using a machine learning-derived lactylation signature for breast cancer prognosis.

BACKGROUND: Breast cancer is a heterogeneous malignancy with complex molecular characteristics, making accurate prognostication and treatment stratifi...

Predicting central lymph node metastasis in papillary thyroid microcarcinoma: a breakthrough with interpretable machine learning.

OBJECTIVE: To develop and validate an interpretable machine learning (ML) model for the preoperative prediction of central lymph node metastasis (CLNM...

Construction of a stromal cell-related prognostic signature based on a 101-combination machine learning framework for predicting prognosis and immunotherapy response in triple-negative breast cancer.

BACKGROUND: Triple-negative breast cancer (TNBC) is a highly aggressive subtype with limited therapeutic targets and poor immunotherapy outcomes. The ...

Construction of a prognostic model for endometrial cancer related to programmed cell death using WGCNA and machine learning algorithms.

BACKGROUND: Programmed cell death (PCD) refers to a regulated and active process of cellular demise, initiated by specific biological signals. PCD pla...