Oncology/Hematology

Chemotherapy

Latest AI and machine learning research in chemotherapy for healthcare professionals.

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Deep learning inference of universal dormancy pseudotime reveals the cellular targets of anti-cancer therapies

Controlled exit from and re-entry into the cell cycle is essential for multi-cellular life, while ab...

High throughput quantitative tracking of single parasite in Plasmodium falciparum

New systematic profiling of drug effects is in urgent demand due to limitations in existing drug ass...

Spatially distinct chromatin compaction states predict neoadjuvant chemotherapy resistance in Triple Negative Breast Cancer

Organisation and dynamics of chromatin play a key role in regulation of cell state and function. In ...

A Druggable Tumor Suppressor and Leukemic Stem Cell Marker

Acute myeloid leukemia (AML) often enters remission after chemotherapy but frequently relapses due t...

VaxjoGNN: A Graph Neural Network for Ontology-Grounded Vaccine Adjuvant Recommendation

The selection of an effective adjuvant is a critical bottleneck in vaccine development, particularly...

A Lung CT Foundation Model Facilitating Disease Diagnosis and Medical Imaging

The concomitant development and evolution of lung computed tomography (CT) and artificial intelligen...

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...

Robust cancer crowdfunding predictions: Leveraging large language models and machine learning for success analysis

In the field of medical crowdfunding prediction, traditional statistical methods have long been the ...

Deep Learning on Histopathological Images to Predict Breast Cancer Recurrence Risk and Chemotherapy Benefit

Genomic testing has transformed treatment decisions for hormone receptor-positive, HER2-negative (HR...

Dissecting the genetic complexity of myalgic encephalomyelitis/chronic fatigue syndrome via deep learning-powered genome analysis

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex, heterogeneous, and systemi...

A comparative analysis of dengue, chikungunya, and Zika in a pediatric cohort over 18 years

Dengue, chikungunya, and Zika are diseases of major human concern. Differential diagnosis is complic...

Transcriptomics-Driven Machine Learning Models Accurately Predict Chemotherapy Response in Muscle-invasive Bladder Cancer

Muscle-invasive bladder cancer (MIBC) is associated with poor predictability of response to cisplati...

Deep Learning-Based Risk Prediction Model for Major Adverse Cardiovascular Events in Long-Term Breast Cancer Survivors

Clinical practice guidelines recommend cardiovascular toxicity risk restratification including evalu...

PyTMLE: A Flexible Python Library for Targeted Estimation of Survival and Competing Risks using Causal Machine Learning

Targeted estimation offers a robust and unbiased approach for causal inference of the average treatm...

Neuroinflammation distinguishes HLA haplotypes in progressive supranuclear palsy

Progressive supranuclear palsy (PSP) is a neurodegenerative 4R tauopathy clinically presenting with ...

Integration of Gene Expression and Digital Histology to Predict Treatment-Specific Responses in Breast Cancer

Deep learning models applied to digital histology can predict gene expression signatures (GES) and o...

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