Oncology/Hematology

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

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A novel deep learning prognostic system improves survival predictions for stage III non-small cell lung cancer.

BACKGROUND: Accurate prognostic prediction plays a crucial role in the clinical setting. However, th...

Target Convergence Analysis of Cancer-Inspired Swarms for Early Disease Diagnosis and Targeted Collective Therapy.

Sensing and perception is generally a challenging aspect of decision-making. In the nanoscale, howev...

An integrated network representation of multiple cancer-specific data for graph-based machine learning.

Genomic profiles of cancer cells provide valuable information on genetic alterations in cancer. Seve...

Spatial analysis of tumor-infiltrating lymphocytes in histological sections using deep learning techniques predicts survival in colorectal carcinoma.

This study aimed to explore the prognostic impact of spatial distribution of tumor-infiltrating lymp...

Sleep staging classification based on a new parallel fusion method of multiple sources signals.

In the field of medical informatics, sleep staging is a challenging and time consuming task undertak...

Deep learning identification of stiffness markers in breast cancer.

While essential to our understanding of solid tumor progression, the study of cell and tissue mechan...

Automated estimation of cancer cell deformability with machine learning and acoustic trapping.

Cell deformability is a useful feature for diagnosing various diseases (e.g., the invasiveness of ca...

Explainable AI in Diagnosing and Anticipating Leukemia Using Transfer Learning Method.

White blood cells (WBCs) are blood cells that fight infections and diseases as a part of the immune ...

A novel liver cancer diagnosis method based on patient similarity network and DenseGCN.

Liver cancer is the main malignancy in terms of mortality rate, accurate diagnosis can help the trea...

Predictive models for clinical decision making: Deep dives in practical machine learning.

The deployment of machine learning for tasks relevant to complementing standard of care and advancin...

Hybrid Loss-Constrained Lightweight Convolutional Neural Networks for Cervical Cell Classification.

Artificial intelligence (AI) technologies have resulted in remarkable achievements and conferred mas...

Gradient tree boosting and network propagation for the identification of pan-cancer survival networks.

Cancer survival prediction is typically done with uninterpretable machine learning techniques, e.g.,...

Histopathology-Based Diagnosis of Oral Squamous Cell Carcinoma Using Deep Learning.

Oral squamous cell carcinoma (OSCC) is prevalent around the world and is associated with poor progno...

Deep learning-based prediction of molecular cancer biomarkers from tissue slides: A new tool for precision oncology.

Molecular tests are necessary to stratify cancer patients for targeted therapy. However, high cost a...

Artificial intelligence to identify genetic alterations in conventional histopathology.

Precision oncology relies on the identification of targetable molecular alterations in tumor tissues...

Finding a Suitable Class Distribution for Building Histological Images Datasets Used in Deep Model Training-The Case of Cancer Detection.

The class distribution of a training dataset is an important factor which influences the performance...

Robot-assisted thoracic surgery for intercostal cavernous hemangioma.

Intercostal cavernous hemangioma is extremely rare among benign vascular tumors. Achieving a definit...

Effects of Multi-Omics Characteristics on Identification of Driver Genes Using Machine Learning Algorithms.

Cancer is a complex disease caused by genomic and epigenetic alterations; hence, identifying meaning...

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