Oncology/Hematology

Lung Cancer

Latest AI and machine learning research in lung cancer for healthcare professionals.

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Showing 1639-1659 of 7,612 articles
Convolutional Neural Networks in Predicting Nodal and Distant Metastatic Potential of Newly Diagnosed Non-Small Cell Lung Cancer on FDG PET Images.

The purpose of this study was to assess, by analyzing features of the primary tumor with F-FDG PET,...

Apr 2020 32348182
Analysis of gene expression profiles of lung cancer subtypes with machine learning algorithms.

Lung cancer is one of the most common cancer types worldwide and causes more than one million deaths...

Apr 2020 32360590
A cross-modal 3D deep learning for accurate lymph node metastasis prediction in clinical stage T1 lung adenocarcinoma.

OBJECTIVES: The evaluation of lymph node (LN) status by radiologists based on preoperative computed ...

Apr 2020 32387813
Perioperative margin detection in basal cell carcinoma using a deep learning framework: a feasibility study.

PURPOSE: Basal cell carcinoma (BCC) is the most commonly diagnosed cancer and the number of diagnosi...

Apr 2020 32323209
A comparative study of machine learning and deep learning algorithms to classify cancer types based on microarray gene expression data.

Cancer classification is a topic of major interest in medicine since it allows accurate and efficien...

Apr 2020 33816921
Cov_FB3D: A De Novo Covalent Drug Design Protocol Integrating the BA-SAMP Strategy and Machine-Learning-Based Synthetic Tractability Evaluation.

drug design actively seeks to use sets of chemical rules for the fast and efficient identification ...

Apr 2020 32233478
DeepDose: Towards a fast dose calculation engine for radiation therapy using deep learning.

We present DeepDose, a deep learning framework for fast dose calculations in radiation therapy. Give...

Apr 2020 32053803
Deep learning-based radiomic features for improving neoadjuvant chemoradiation response prediction in locally advanced rectal cancer.

Radiomic features achieve promising results in cancer diagnosis, treatment response prediction, and ...

Apr 2020 32092710
Ontologies in radiation oncology.

Ontologies are a formal, computer-compatible method for representing scientific knowledge about a gi...

Apr 2020 32247963
Comparison of Robot-Assisted and Laparoscopic Partial Nephrectomy for Completely Endophytic Renal Tumors: A High-Volume Center Experience.

To compare the perioperative, functional, and oncologic outcomes of robot-assisted partial nephrect...

Mar 2020 32098491
Identification of Non-Small Cell Lung Cancer Sensitive to Systemic Cancer Therapies Using Radiomics.

PURPOSE: Using standard-of-care CT images obtained from patients with a diagnosis of non-small cell ...

Mar 2020 32198149
Triple-Negative Breast Cancer: A Review of Conventional and Advanced Therapeutic Strategies.

Triple-negative breast cancer (TNBC) cells are deficient in estrogen, progesterone and ERBB2 recepto...

Mar 2020 32245065
Overall survival prediction of non-small cell lung cancer by integrating microarray and clinical data with deep learning.

Non-small cell lung cancer (NSCLC) is one of the most common lung cancers worldwide. Accurate progno...

Mar 2020 32170141
A Novel System for Functional Determination of Variants of Uncertain Significance using Deep Convolutional Neural Networks.

Many drugs are developed for commonly occurring, well studied cancer drivers such as vemurafenib for...

Mar 2020 32144301
CT-based radiomics and machine learning to predict spread through air space in lung adenocarcinoma.

PURPOSE: Spread through air space (STAS) is a novel invasive pattern of lung adenocarcinoma and is a...

Feb 2020 32112116
The Impact of Artificial Intelligence and Machine Learning in Radiation Therapy: Considerations for Future Curriculum Enhancement.

Artificial intelligence (AI) and machine learning (ML) approaches have caught the attention of many ...

Feb 2020 32115386
Machine learning on genome-wide association studies to predict the risk of radiation-associated contralateral breast cancer in the WECARE Study.

The purpose of this study was to identify germline single nucleotide polymorphisms (SNPs) that optim...

Feb 2020 32106268
Feature-shared adaptive-boost deep learning for invasiveness classification of pulmonary subsolid nodules in CT images.

PURPOSE: In clinical practice, invasiveness is an important reference indicator for differentiating ...

Feb 2020 32020649
Comparison of statistical machine learning models for rectal protocol compliance in prostate external beam radiation therapy.

PURPOSE: Limiting the dose to the rectum can be one of the most challenging aspects of creating a do...

Feb 2020 31981427
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