Oncology/Hematology

Latest AI and machine learning research in oncology/hematology for healthcare professionals.

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Brain tumor classification based on neural architecture search.

Brain tumor is a life-threatening disease and causes about 0.25 million deaths worldwide in 2020. Ma...

Self-Supervised Multi-Modal Hybrid Fusion Network for Brain Tumor Segmentation.

Accurate medical image segmentation of brain tumors is necessary for the diagnosing, monitoring, and...

Novel artificial intelligent transformer U-NET for better identification and management of prostate cancer.

Advancements in artificial intelligence (AI) strengthens life-altering technology that can not only ...

Artificial intelligence in lung cancer: current applications and perspectives.

Artificial intelligence (AI) has been a very active research topic over the last years and thoracic ...

OrganoID: A versatile deep learning platform for tracking and analysis of single-organoid dynamics.

Organoids have immense potential as ex vivo disease models for drug discovery and personalized drug ...

Multiple instance neural networks based on sparse attention for cancer detection using T-cell receptor sequences.

Early detection of cancers has been much explored due to its paramount importance in biomedical fiel...

Deep learning-based image analysis predicts PD-L1 status from H&E-stained histopathology images in breast cancer.

Programmed death ligand-1 (PD-L1) has been recently adopted for breast cancer as a predictive biomar...

NAVIGATOR: an Italian regional imaging biobank to promote precision medicine for oncologic patients.

NAVIGATOR is an Italian regional project boosting precision medicine in oncology with the aim of mak...

Deep learning model for breast cancer diagnosis based on bilateral asymmetrical detection (BilAD) in digital breast tomosynthesis images.

The purpose of this study was to develop a deep learning model to diagnose breast cancer by embeddin...

Patient-specific transfer learning for auto-segmentation in adaptive 0.35 T MRgRT of prostate cancer: a bi-centric evaluation.

BACKGROUND: Online adaptive radiation therapy (RT) using hybrid magnetic resonance linear accelerato...

Microfluidics guided by deep learning for cancer immunotherapy screening.

Immunocyte infiltration and cytotoxicity play critical roles in both inflammation and immunotherapy....

Deep learning to estimate durable clinical benefit and prognosis from patients with non-small cell lung cancer treated with PD-1/PD-L1 blockade.

Different biomarkers based on genomics variants have been used to predict the response of patients t...

High-content video flow cytometry with digital cell filtering for label-free cell classification by machine learning.

Recent development of imaging flow cytometry (IFC) has enabled the measurements of single cells with...

Computer-aided detection and prognosis of colorectal cancer on whole slide images using dual resolution deep learning.

PURPOSE: Rapid diagnosis and risk stratification can provide timely treatment for colorectal cancer ...

Deep learning application of the discrimination of bone marrow aspiration cells in patients with myelodysplastic syndromes.

Myelodysplastic syndromes (MDS) are a group of hematologic neoplasms accompanied by dysplasia of the...

Fluorescence-guided extended pelvic lymphadenectomy during robotic radical prostatectomy.

We evaluated and described the impact of prostatic indocyanine green (ICG) injection on extended pel...

Is it possible to use low-dose deep learning reconstruction for the detection of liver metastases on CT routinely?

OBJECTIVES: To compare the image quality and hepatic metastasis detection of low-dose deep learning ...

Accurate prediction of histological grading of intraductal papillary mucinous neoplasia using deep learning.

BACKGROUND: Risk stratification and recommendation for surgery for intraductal papillary mucinous ne...

Deep learning model to predict Epstein-Barr virus associated gastric cancer in histology.

The detection of Epstein-Barr virus (EBV) in gastric cancer patients is crucial for clinical decisio...

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