Oncology/Hematology

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

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Breast Tumor Diagnosis Based on Molecular Learning Vector Quantization Neural Networks.

DNA nanotechnology plays a crucial role in precise cancer medicine. Currently, molecular logic circu...

Leukemia detection and classification using computer-aided diagnosis system with falcon optimization algorithm and deep learning.

Leukemia is a type of blood tumour that occurs because of abnormal enhancement in WBCs (white blood ...

Multi-omics features of immunogenic cell death in gastric cancer identified by combining single-cell sequencing analysis and machine learning.

Gastric cancer (GC) is a prevalent malignancy with high mortality rates. Immunogenic cell death (ICD...

The Use of Artificial Intelligence Technologies in Cancer Care.

Artificial intelligence (AI) is already an essential tool in the handling of large data sets in epid...

Benchmarking deep learning-based low-dose CT image denoising algorithms.

BACKGROUND: Long-lasting efforts have been made to reduce radiation dose and thus the potential radi...

[Development and validation of a tool for the systematic identification of social vulnerabilities in cancer patients: the DEFCO tool].

INTRODUCTION: Literature suggests that patients from deprived backgrounds are less likely to adhere ...

The BCPM method: decoding breast cancer with machine learning.

Breast cancer prediction and diagnosis are critical for timely and effective treatment, significantl...

Intelligence computational analysis of letrozole solubility in supercritical solvent via machine learning models.

Supercritical fluids (SCFs) can be used to prepare drugs nanoparticles with improved solubility. SCF...

Longitudinal deep neural networks for assessing metastatic brain cancer on a large open benchmark.

The detection and tracking of metastatic cancer over the lifetime of a patient remains a major chall...

The emerging role of AI in enhancing intratumoral immunotherapy care.

The emergence of immunotherapy (IO), and more recently intratumoral IO presents a novel approach to ...

Economic Evaluation of a Novel Lung Cancer Diagnostic in a Population of Patients with a Positive Low-Dose Computed Tomography Result.

Early detection of lung cancer is crucial for improving patient outcomes. Although advances in diag...

Machine learning-based identification of an immunotherapy-related signature to enhance outcomes and immunotherapy responses in melanoma.

BACKGROUND: Immunotherapy has revolutionized skin cutaneous melanoma treatment, but response variabi...

From whole-slide image to biomarker prediction: end-to-end weakly supervised deep learning in computational pathology.

Hematoxylin- and eosin-stained whole-slide images (WSIs) are the foundation of diagnosis of cancer. ...

CBAM-RIUnet: Breast Tumor Segmentation With Enhanced Breast Ultrasound and Test-Time Augmentation.

This study addresses the challenge of precise breast tumor segmentation in ultrasound images, crucia...

Deciphering the cytotoxicity of micro- and nanoplastics in Caco-2 cells through meta-analysis and machine learning.

Plastic pollution, driven by micro- and nanoplastics (MNPs), poses a major environmental threat, exp...

RCC-Supporter: supporting renal cell carcinoma treatment decision-making using machine learning.

BACKGROUND: The population diagnosed with renal cell carcinoma, especially in Asia, represents 36.6%...

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