Oncology/Hematology

Breast Cancer

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

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Predicting MammaPrint Recurrence Risk from Breast Cancer Pathological Images Using a Weakly Supervised Transformer

Recurrence related to poor prognosis is a leading cause of mortality in patients with breast cancer ...

Identifying tissue states by spatial protein patterns related to chemotherapy response in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is an aggressive malignancy with limited targeted therapies and...

Single-cell RNA sequencing and large-scale bulk combination with machine learning reveal gastric cancer-related macrophage heterogeneity

The tumor microenvironment (TME) significantly impacts cancer progression and overall patient surviv...

Deep Learning Bridges Histology and Transcriptomics to Predict Molecular Subtypes and Outcomes in Muscle-Invasive Bladder Cancer

Muscle-Invasive Bladder Cancer (MIBC) is a heterogeneous disease with distinct molecular subtypes in...

USP-ddG: A Unified Structural Paradigm with Data Efficacy and Mixture-of-Experts for Predicting Mutational Effects on Protein-Protein Interactions

Accurately estimating changes in binding free energy (ΔΔG) is essential for understanding protein-pr...

A machine learning framework for supervised treatment response prediction from tumor transcriptomics: A large-scale pan-cancer study

Precision oncology aims to guide treatment decisions using biomarkers. While DNA-based panels are in...

Integrative spatial multi-omics reveals prognostic tumor niches in female genital tumors

Female genital tumors (FGTs), including ovarian, endometrial, and cervical cancers, pose a major glo...

Lab-in-the-loop therapeutic antibody design with deep learning

Therapeutic antibody design is a complex multi-property optimization problem with substantial promis...

From Big Data to Small Scales: Machine Learning Enhances Microclimate Model Predictions

1. Microclimates are critical for understanding how organisms interact with their environments, infl...

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...

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...

Impact of a machine learning-powered algorithm on pathologist HER2 IHC scoring in breast cancer

HER2 expression level is a key factor in determining the optimal treatment course for breast cancer ...

Performance of an artificial intelligence foundation model for prostate radiotherapy segmentation

Artificial intelligence (AI) foundation models such as Segment Anything Model 2 (SAM 2) offer potent...

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 ...

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