AI Medical Compendium Topic:
Neoplasms

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Rethinking Breast Cancer Diagnosis through Deep Learning Based Image Recognition.

Sensors (Basel, Switzerland)
This paper explored techniques for diagnosing breast cancer using deep learning based medical image recognition. X-ray (Mammography) images, ultrasound images, and histopathology images are used to improve the accuracy of the process by diagnosing br...

Artificial intelligence for diagnosing neoplasia on digital cholangioscopy: development and multicenter validation of a convolutional neural network model.

Endoscopy
BACKGROUND: We aimed to develop a convolutional neural network (CNN) model for detecting neoplastic lesions during real-time digital single-operator cholangioscopy (DSOC) and to clinically validate the model through comparisons with DSOC expert and n...

LGEANet: LSTM-global temporal convolution-external attention network for respiratory motion prediction.

Medical physics
PURPOSE: To develop a deep learning network that treats the three-dimensional respiratory motion signals as a whole and considers the inter-dimensional correlation between signals of different directions for accurate respiratory tumor motion predicti...

Adaptive fuzzy control of drug delivery in cancer treatment using combination of chemotherapy and antiangiogenic therapy.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
This paper introduces the adaptive fuzzy control scheme as a promising control technique for cancer treatment from a theoretical point of view. A mathematical model describing the dynamics of tumor growth under the drug interventions of chemotherapy ...

DeepInsight-3D architecture for anti-cancer drug response prediction with deep-learning on multi-omics.

Scientific reports
Modern oncology offers a wide range of treatments and therefore choosing the best option for particular patient is very important for optimal outcome. Multi-omics profiling in combination with AI-based predictive models have great potential for strea...

A deep learning approach reveals unexplored landscape of viral expression in cancer.

Nature communications
About 15% of human cancer cases are attributed to viral infections. To date, virus expression in tumor tissues has been mostly studied by aligning tumor RNA sequencing reads to databases of known viruses. To allow identification of divergent viruses ...

Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response.

International journal of molecular sciences
Immunotherapy constitutes a paradigm shift in cancer treatment. Its FDA approval for several indications has yielded improved prognosis for cases where traditional therapy has shown limited efficiency. However, many patients still fail to benefit fro...

Predicting the Survival of Patients With Cancer From Their Initial Oncology Consultation Document Using Natural Language Processing.

JAMA network open
IMPORTANCE: Predicting short- and long-term survival of patients with cancer may improve their care. Prior predictive models either use data with limited availability or predict the outcome of only 1 type of cancer.

3D dose prediction for Gamma Knife radiosurgery using deep learning and data modification.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: To develop a machine learning-based, 3D dose prediction methodology for Gamma Knife (GK) radiosurgery. The methodology accounts for cases involving targets of any number, size, and shape.

Utilization of robotics in pediatric surgical oncology.

Seminars in pediatric surgery
Despite increasing implementation of robotic surgery and minimally invasive techniques within adult surgical oncology and pediatric general surgery, the utilization of robotic-assisted resections for pediatric tumors has been met with controversy. Th...