Other Cancers

Machine learning prediction of overall survival in prostate adenocarcinoma using ensemble techniques.

Prostate adenocarcinoma (PAC) is a complex and common cancer in males and is one of the leading caus...

An interpretable machine learning model based on computed tomography radiomics for predicting programmed death ligand 1 expression status in gastric cancer.

BACKGROUND: Programmed death ligand 1 (PD-L1) expression status, closely related to immunotherapy ou...

Deep learning radiomics for the prediction of epidermal growth factor receptor mutation status based on MRI in brain metastasis from lung adenocarcinoma patients.

BACKGROUND: Early and accurate identification of epidermal growth factor receptor (EGFR) mutation st...

Lung cancer detection with machine learning classifiers with multi-attribute decision-making system and deep learning model.

Diseases of the airways and the other parts of the lung cause chronic respiratory diseases. The majo...

The Role of AI in Lymphoma: An Update.

Malignant lymphomas encompass a range of malignancies with incidence rising globally, particularly w...

Development and validation of an interpretable machine learning model for predicting the risk of hepatocellular carcinoma in patients with chronic hepatitis B: a case-control study.

BACKGROUND: The aim of this study was to develop and internally validate an interpretable machine le...

Unraveling the power of NAP-CNB's machine learning-enhanced tumor neoantigen prediction.

In this study, we present a proof-of-concept classical vaccination experiment that validates the in ...

Advancing sepsis diagnosis and immunotherapy machine learning-driven identification of stable molecular biomarkers and therapeutic targets.

Sepsis represents a significant global health challenge, necessitating early detection and effective...

GraphSleepFormer: a multi-modal graph neural network for sleep staging in OSA patients.

Obstructive sleep apnea (OSA) is a prevalent sleep disorder. Accurate sleep staging is one of the pr...

Multimodal deep learning for predicting PD-L1 biomarker and clinical immunotherapy outcomes of esophageal cancer.

Although the immune checkpoint inhibitors (ICIs) have demonstrated remarkable anti-tumor efficacy in...

A deep-learning model to predict the completeness of cytoreductive surgery in colorectal cancer with peritoneal metastasis☆.

BACKGROUND: Colorectal cancer (CRC) with peritoneal metastasis (PM) is associated with poor prognosi...

Nano biosensor unlocks tumor derived immune signals for the early detection of ovarian cancer.

Ovarian cancer is a critical health issue for women nowadays. Its impact is significant because of i...

Innovative construction and application of bile duct organoids: Unraveling the complexity of bile duct diseases and potential therapeutic strategies.

The biliary system is crucial for liver function, regulating bile production, secretion, and transpo...

Validation of patient-specific deep learning markerless lung tumor tracking aided by 4DCBCT.

. Tracking tumors with multi-leaf collimators and x-ray imaging can be a cost-effective motion manag...

Direct-to-Treatment Adaptive Radiation Therapy: Live Planning of Spine Metastases Using Novel Cone Beam Computed Tomography.

PURPOSE: Cone beam computed tomography (CBCT)-based online adaptive radiation therapy is carried out...

The accuracy of artificial intelligence in the diagnosis of soft tissue sarcoma: A systematic review and meta-analysis.

Transcriptome analysis reveals the potential role of neural factor EN1 for long-terms survival in estrogen receptor-independent breast cancer.

Breast cancer patients with estrogen receptor-negative (ERneg) status, encompassing triple negative ...

Prediction of tumor spread through air spaces with an automatic segmentation deep learning model in peripheral stage I lung adenocarcinoma.

BACKGROUND: To evaluate the clinical applicability of deep learning (DL) models based on automatic s...

Self-supervised learning reveals clinically relevant histomorphological patterns for therapeutic strategies in colon cancer.

Self-supervised learning (SSL) automates the extraction and interpretation of histopathology feature...

Development and validation of computer-aided detection for colorectal neoplasms using deep learning incorporated with computed tomography colonography.

OBJECTIVES: Computed tomography (CT) colonography is increasingly recognized as a valuable modality ...

Integrating local and global attention mechanisms for enhanced oral cancer detection and explainability.

BACKGROUND AND OBJECTIVE: Early detection of Oral Squamous Cell Carcinoma (OSCC) improves survival r...