AIMC Topic: Neoplasms

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Predicting cancer origins with a DNA methylation-based deep neural network model.

PloS one
Cancer origin determination combined with site-specific treatment of metastatic cancer patients is critical to improve patient outcomes. Existing pathology and gene expression-based techniques often have limited performance. In this study, we develop...

Generation and evaluation of synthetic patient data.

BMC medical research methodology
BACKGROUND: Machine learning (ML) has made a significant impact in medicine and cancer research; however, its impact in these areas has been undeniably slower and more limited than in other application domains. A major reason for this has been the la...

Autonomous Biohybrid Urchin-Like Microperforator for Intracellular Payload Delivery.

Small (Weinheim an der Bergstrasse, Germany)
A magnetic urchin-like microswimmer based on sunflower pollen grain (SPG) that can pierce the cancer cell membrane and actively deliver therapeutic drugs is reported. These drug loaded microperforators are fabricated on a large scale by sequentially ...

SDLDA: lncRNA-disease association prediction based on singular value decomposition and deep learning.

Methods (San Diego, Calif.)
In recent years, accumulating studies have shown that long non-coding RNAs (lncRNAs) not only play an important role in the regulation of various biological processes but also are the foundation for understanding mechanisms of human diseases. Due to ...

Knowledge Graph-Enabled Cancer Data Analytics.

IEEE journal of biomedical and health informatics
Cancer registries collect unstructured and structured cancer data for surveillance purposes which provide important insights regarding cancer characteristics, treatments, and outcomes. Cancer registry data typically (1) categorize each reportable can...

Convolutional Neural Network Can Recognize Drug Resistance of Single Cancer Cells.

International journal of molecular sciences
It is known that single or isolated tumor cells enter cancer patients' circulatory systems. These circulating tumor cells (CTCs) are thought to be an effective tool for diagnosing cancer malignancy. However, handling CTC samples and evaluating CTC se...

Identification of the Facial Features of Patients With Cancer: A Deep Learning-Based Pilot Study.

Journal of medical Internet research
BACKGROUND: Cancer has become the second leading cause of death globally. Most cancer cases are due to genetic mutations, which affect metabolism and result in facial changes.

High quality proton portal imaging using deep learning for proton radiation therapy: a phantom study.

Biomedical physics & engineering express
Purpose; For shoot-through proton treatments, like FLASH radiotherapy, there will be protons exiting the patient which can be used for proton portal imaging (PPI), revealing valuable information for the validation of tumor location in the beam's-eye-...

iTTCA-Hybrid: Improved and robust identification of tumor T cell antigens by utilizing hybrid feature representation.

Analytical biochemistry
In spite of the repertoire of existing cancer therapies, the ongoing recurrence and new cases of cancer poses a challenging health concern that prompts for novel and effective treatment. Cancer immunotherapy represents a promising venue for treatment...

Artificial Intelligence in radiotherapy: state of the art and future directions.

Medical oncology (Northwood, London, England)
Recent advances in computing capability allowed the development of sophisticated predictive models to assess complex relationships within observational data, described as Artificial Intelligence. Medicine is one of the several fields of application a...