Oncology/Hematology

Multi-omics approaches for identifying the PANoptosis signature and prognostic model via a multimachine-learning computational framework for intrahepatic cholangiocarcinoma.

BACKGROUND AND AIMS: The aims of the present study were to characterize the PANoptosis signature in intrahepatic cholangiocarcinoma (ICC) patients, construct a novel model to guide clinical diagnosis and treatment, and further explore the associated molecular mechanisms of drug resistance. APPROACH AND RESULTS: In total, 85 PANoptosis-related genes that possess both PANoptosis and multi-omics feat...

Single-Cell Sequencing-Guided Annotation of Rare Tumor Cells for Deep Learning-Based Cytopathologic Diagnosis of Early Lung Cancer.

Deep learning (DL) models for medical image analysis are majorly bottlenecked by the lack of well-annotated datasets. Bronchoalveolar lavage (BAL) is a minimally invasive procedure to diagnose lung cancer, but BAL cytology suffers from low sensitivity. The success of DL in BAL cytology is rare due to the rarity of exfoliated tumor cells (ETCs) and their subtle morphological differences from normal...

Identifying potential risk genes for clear cell renal cell carcinoma with deep reinforcement learning.

Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of renal cell carcinoma. However, our understanding of ccRCC risk genes remains lim...

Accurate bladder cancer diagnosis using ensemble deep leaning.

There are an estimated 1.3 million cases of cancer globally each year, making it one of the most serious types of urinary tract cancer. The methods us...

An integrated approach of feature selection and machine learning for early detection of breast cancer.

Breast cancer ranks among the most prevalent cancers in women globally, with its treatment efficacy heavily reliant on the early identification and di...

Prediction of postoperative intensive care unit admission with artificial intelligence models in non-small cell lung carcinoma.

BACKGROUND: There is no standard practice for intensive care admission after non-small cell lung cancer surgery. In this study, we aimed to determine ...

Multiple instance learning-based prediction of programmed death-ligand 1 (PD-L1) expression from hematoxylin and eosin (H&E)-stained histopathological images in breast cancer.

Programmed death-ligand 1 (PD-L1) is an important biomarker increasingly used as a predictive marker in breast cancer immunotherapy. Immunohistochemic...

Nasopharyngeal cancer screening and immunotherapy efficacy evaluation based on plasma separation combined with label-free SERS technology.

BACKGROUND: In recent years, significant progress has been made in the treatment of nasopharyngeal carcinoma (NPC). The application of immunotherapy, ...

Self-supervised network predicting neoadjuvant chemoradiotherapy response to locally advanced rectal cancer patients.

Radiographic imaging is a non-invasive technique of considerable importance for evaluating tumor treatment response. However, redundancy in CT data an...

Sonopermeation combined with stroma normalization enables complete cure using nano-immunotherapy in murine breast tumors.

Nano-immunotherapy shows great promise in improving patient outcomes, as seen in advanced triple-negative breast cancer, but it does not cure the dise...

Designing Clinical Trials for Patients With Rare Cancers: Connecting the Zebras.

The field of rare cancer research is rapidly transforming, marked by significant progress in clinical trials and treatment strategies. Rare cancers, a...

Machine Learning and Structural Dynamics-Based Approach to Reveal Molecular Mechanism of PTEN Missense Mutations Shared by Cancer and Autism Spectrum Disorder.

Missense mutations in oncogenic proteins that are concurrently associated with neurodevelopmental disorders have garnered significant attention. Phosp...

Towards improved prescription metrics in novel radiotherapy techniques: a machine learning study.

FLASH radiotherapy (RT), microbeam RT (MRT) and minibeam RT (MBRT) are novel RT techniques that have been shown to reduce normal tissue complication p...

Identification of Recurrence-associated Gene Signatures and Machine Learning-based Prediction in IDH-Wildtype Histological Glioblastoma.

Glioblastoma (GBM) is a highly aggressive brain tumor with frequent recurrence, yet the molecular mechanisms driving recurrence remain poorly understo...

ALL diagnosis: can efficiency and transparency coexist? An explainble deep learning approach.

Acute Lymphoblastic Leukemia (ALL) is a life-threatening malignancy characterized by its aggressive progression and detrimental effects on the hematop...

Integrating machine learning driven virtual screening and molecular dynamics simulations to identify potential inhibitors targeting PARP1 against prostate cancer.

Prostate cancer (PC) is one of the most common types of malignancies in men, with a noteworthy increase in newly diagnosed cases in recent years. PARP...

A hybrid learning network with progressive resizing and PCA for diagnosis of cervical cancer on WSI slides.

Current artificial intelligence (AI) trends are revolutionizing medical image processing, greatly improving cervical cancer diagnosis. Machine learnin...

Comparative study of XGBoost and logistic regression for predicting sarcopenia in postsurgical gastric cancer patients.

The use of machine learning (ML) techniques, particularly XGBoost and logistic regression, to predict sarcopenia among postsurgical gastric cancer pat...

Development and validation of a nomogram model of lung metastasis in breast cancer based on machine learning algorithm and cytokines.

BACKGROUND: The relationship between cytokines and lung metastasis (LM) in breast cancer (BC) remains unclear and current clinical methods for identif...

Unique Microbial Characterisation of Oesophageal Squamous Cell Carcinoma Patients with Different Dietary Habits Based on Light Gradient Boosting Machine Learning Classifier.

: The microbiome plays an important role in cancer, but the relationship between dietary habits and the microbiota in oesophageal squamous cell carcin...