Oncology/Hematology

Colon Cancer

Latest AI and machine learning research in colon cancer for healthcare professionals.

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A large language model for predicting pancreatic ductal adenocarcinoma patients from blood-derived exosomal transcriptomics data

Traditional machine learning approaches for text or sequence classification rely on converting textu...

Integrative transcriptomic analysis identifies miR-642a-5p as a regulator of POFUT1 expression in colon cancer

Colorectal cancer (CRC) is one of the most common and deadly cancers worldwide, underscoring the urg...

An integrated platform for high-throughput phenospace learning of 3D multilineage organoid systems

Complex multilineage organoid systems lack quantitative phenotyping methods preserving spatial archi...

Self-supervised AI reveals a lethal discohesive phenotype in lung adenocarcinoma

Applications of artificial intelligence (AI) to histopathology are now common, but most require supe...

Batch-Harmonized Machine Learning Framework for Cross-Cohort RNA Biomarker Discovery in Pancreatic Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) lacks reliable prognostic biomarkers. RNA-based signatures s...

A Multi-Modal Transfer Learning Framework to Reduce Health Disparities in Prostate Adenocarcinoma

Prostate cancer is the second most common cancer in men across the United States, of which prostate ...

Unraveling miRNA-Driven DNA Damage Response Networks in Pancreatic Adenocarcinoma: A Multi-Omics and Machine Learning Approach

Due to the late detection, aggressive nature, and paucity of treatment options, pancreatic adenocarc...

ROSIE-Enabled Spatial Mapping Reveals Architectural Fragmentation and Immune Reprogramming in Lung Adenocarcinoma Evolution

The progression of lung adenocarcinoma (LUAD) from precancerous lesions to invasive carcinoma entail...

lncAPNet enables the deciphering of lncRNA–mRNA connections in patient transcriptomic data

Long non-coding RNAs (lncRNAs) regulate gene expression through chromatin remodeling, transcriptiona...

Counterfactual Diffusion Models for Interpretable Explanations of Artificial Intelligence Models in Pathology

Deep learning can extract predictive and prognostic biomarkers from histopathology whole slide image...

Exploring Stress-Induced Neural Circuit Remodeling through Data-Driven Analysis and Artificial Neural Network Simulation

Chronic stress induces behavioral rigidity and neural circuit remodeling, yet the underlying computa...

Assessing Genotype-Phenotype Correlations with Deep Learning in Colorectal Cancer: A Multi-Centric Study

Deep Learning (DL) has emerged as a powerful tool to predict genetic biomarkers directly from digiti...

AI-HOPE: An AI-Driven conversational agent for enhanced clinical and genomic data integration in precision medicine research

Introduction: The increasing complexity of clinical cancer research necessitates the development of ...

Segmentation-Free Pretherapeutic Assessment of BRAF-Status in Pediatric Low-Grade Gliomas

BRAF status is crucial for treating pediatric low-grade gliomas (pLGG) and can be assessed non-invas...

Establishment of in silico prediction of adjuvant chemotherapy response from active mitotic gene signature in non-small cell lung cancer

Conventional chemotherapeutics exploit cancer’s hallmark of active cell cycling, primarily targeting...

Pancreatic cancer risk prediction using deep sequential modeling of longitudinal diagnostic and medication records

Pancreatic ductal adenocarcinoma (PDAC) is a rare, aggressive cancer often diagnosed late with low s...

Patient Attitudes Toward Artificial Intelligence in Cancer Care: A Scoping Review

To synthesize existing literature on patient attitudes toward AI in cancer care and identify knowled...

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