Oncology/Hematology

Lung Cancer

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

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Prediction of Binding Affinity for ErbB Inhibitors Using Deep Neural Network Model with Morgan Fingerprints as Features

The ErbB receptor family, including EGFR and HER2, plays a crucial role in cell growth and surviva...

End-to-End Deep Learning for Interior Tomography with Low-Dose X-ray CT

Objective: There exist several X-ray computed tomography (CT) scanning strategies to reduce a radi...

Mechanistic modeling and machine learning identifies optimum radiotherapy schedules to prevent treatment-induced metastasis

Lung cancer patients often experience increased metastasis formation after radiotherapy. However, it...

Structural similarities reveal an expansive conotoxin family with a two-finger toxin fold

Venomous animals have evolved a diverse repertoire of toxins with considerable pharmaceutical potent...

RNA liquid biopsy via nanopore sequencing for novel biomarker discovery and cancer early detection

Liquid biopsies detect disease noninvasively by profiling cell-free nucleic acids that are secreted ...

A Deep Learning-based Method for Drug Molecule Representation and Property Prediction

Accurately and robustly representing drug molecule features, prediction of drug-target biomacromolec...

Integrative network modeling of colorectal cancer reveals diagnostic signatures and therapeutic targets

Emerging evidence suggests that the interplay between multiple signaling pathways and the immune mic...

Deep Learning for Molecular and Genomic Characterization of Lung Cancer in Never-Smokers Using Hematoxylin and Eosin-Stained Images

Despite promising results in using deep learning to infer genetic features from histological whole-s...

Transcriptional Signatures of Field Cancerization in Gastric Cancer

The high rate of local recurrence in gastric adenocarcinoma (GA) suggests that carcinogenesis is not...

Interpretable Deep Learning Reveals Biologically Relevant Spatial Gene Expression Patterns in Lung Tumors and their Microenvironment

Lung adenocarcinoma (LUAD), the most common subtype of non–small cell lung cancer (NSCLC) exhibits p...

Lung Adenocarcinoma Just Desserts: An Expanding Pie of Activating Oncogenes or a Layer Cake of Integrated Alterations

The molecular landscape of lung adenocarcinoma (LUAD) is often summarized as a “pie chart” of driver...

Non-Invasive Diagnostic Evaluation of Urinary Exosomal Let-7c Cluster Expression in Bladder Cancer Using Machine Learning Approaches

Bladder cancer (BCa) diagnosis typically relies on invasive cystoscopy, which is effective but costl...

Deep Learning-Based Classification of Colorectal Cancer in Histopathology Images for Category Detection

Accurate and timely diagnosis of colorectal cancer (CRC) is essential for effective treatment and be...

Histology-guided 3D virtual staining of microCT-imaged lung tissue via deep learning

Histologically stained tissue sections are considered the gold standard for studying microscopic ana...

Machine learning-based definition of cellular senescence reveals pro-senescence potential implication in lung adenocarcinoma

Despite growing evidence implicating cellular senescence in tumor progression, methodological challe...

Systems biology framework for rational design of operational conditions for in vitro / in vivo translation of microphysiological systems

Preclinical models are used extensively to study diseases and potential therapeutic treatments. Comp...

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...

Predictive power of different Akkermansia phylogroups in clinical response to PD-1 blockade against non-small cell lung cancer

Immune checkpoint blockade has emerged as a promising form of cancer therapy. However, only some pat...

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