Oncology/Hematology

Other Cancers

Latest AI and machine learning research in other cancers for healthcare professionals.

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Machine Learning for Genomic Profiling and Drug Discovery in Personalised Lung Cancer Therapeutics.

Lung cancer is a prevalent and lethal malignancy characterised by the uncontrolled growth of abnorma...

SLC3A2 as a key anoikis-related gene for prognosis and tumor microenvironment remodeling in melanoma.

OBJECTIVE: Anoikis, a form of programmed cell death triggered by detachment from the extracellular m...

Diffusion-weighted imaging in rectal cancer MRI from theory to practice.

Diffusion-weighted imaging (DWI) has become a cornerstone of high-resolution rectal MRI, providing c...

Solving Mazes of Organelle-Targeted Therapies with DNA Nanomachines.

Despite decades of research, cancer remains a growing global health challenge. Nanomaterials-based t...

SPP1 promotes malignant characteristics and drug resistance in hepatocellular carcinoma by activating fatty acid metabolic pathway.

Hepatocellular carcinoma (HCC) progression and prognosis are influenced by various molecular markers...

USP5-Mediated PD-L1 deubiquitination regulates immunotherapy efficacy in melanoma.

BACKGROUND: The role of post-translational modifications(PTMs) in PD-L1-mediated immune resistance a...

Deep learning on routine full-breast mammograms enhances lymph node metastasis prediction in early breast cancer.

With the shift toward de-escalating surgery in breast cancer, prediction models incorporating imagin...

Machine learning analysis of survival outcomes in breast cancer patients treated with chemotherapy, hormone therapy, surgery, and radiotherapy.

Breast cancer continues to be a leading cause of death among women in the world. The prediction of s...

Recurrence prediction of invasive ductal carcinoma from preoperative contrast-enhanced computed tomography using deep convolutional neural network.

Predicting the risk of breast cancer recurrence is crucial for guiding therapeutic strategies, inclu...

Recent advancement in endoscopic diagnosis for risk stratification of gastric cancer.

Approximately 90% of cases of gastric cancer (GC) are caused by Helicobacter pylori infection, and s...

Machine learning-based prediction model for post-ERCP cholangitis in patients with malignant biliary obstruction: a retrospective multicenter study.

BACKGROUND: Endoscopic retrograde cholangiopancreatography (ERCP) is the preferred palliative treatm...

Single-cell spatial transcriptomics reveals immunotherapy-driven bone marrow niche remodeling in AML.

Given the graft-versus-leukemia effect observed with allogeneic hematopoietic stem cell transplantat...

Transformer optimization with meta learning on pathology images for breast cancer lymph node micrometastasis.

Lymph node micro-metastasis represents the initial stage of breast cancer spread or metastasis. Howe...

Machine learning for synchronous bone metastasis risk prediction in high grade lung neuroendocrine carcinoma.

Bone metastasis (BM) is common in high-grade lung neuroendocrine tumors (NETs). This study aimed to ...

Metastability and Ostwald step rule in the crystallisation of diamond and graphite from molten carbon.

Experimental challenges in determining the phase diagram of carbon at temperatures and pressures nea...

Leveraging machine learning models to evaluate immune infiltration in the ovarian cancer microenvironment: a single-cell analysis approach.

BACKGROUND: The prognosis of ovarian cancer is closely related to the degree of immune cell infiltra...

Performance of AI Chatbots in Preliminary Diagnosis of Maxillofacial Pathologies.

BACKGROUND Artificial intelligence (AI) has shown significant potential in transforming healthcare b...

Computation strategies and clinical applications in neoantigen discovery towards precision cancer immunotherapy.

Neoantigens, which are tumor-specific peptides generated by malignant cells, can be presented to T c...

Integrative multimodal ultrasound and radiomics for early prediction of neoadjuvant therapy response in breast cancer: a clinical study.

PURPOSE: This study aimed to develop an early predictive model for neoadjuvant therapy (NAT) respons...

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