Lung Cancer

Discovery of Dual FGFR4 and EGFR Inhibitors by Machine Learning and Biological Evaluation.

Kinase inhibitors are widely used in antitumor research, but there are still many problems such as d...

Applications of artificial intelligence and deep learning in molecular imaging and radiotherapy.

This brief review summarizes the major applications of artificial intelligence (AI), in particular d...

Deep Learning to Estimate RECIST in Patients with NSCLC Treated with PD-1 Blockade.

Real-world evidence (RWE), conclusions derived from analysis of patients not treated in clinical tri...

Simple low-cost approaches to semantic segmentation in radiation therapy planning for prostate cancer using deep learning with non-contrast planning CT images.

PURPOSE: Deep learning has shown great efficacy for semantic segmentation. However, there are diffic...

Increasing tendency of urine protein is a risk factor for rapid eGFR decline in patients with CKD: A machine learning-based prediction model by using a big database.

Artificial intelligence is increasingly being adopted in medical fields to predict various outcomes....

Fluence Map Prediction Using Deep Learning Models - Direct Plan Generation for Pancreas Stereotactic Body Radiation Therapy.

Treatment planning for pancreas stereotactic body radiation therapy (SBRT) is a difficult and time-...

Deep learning-based metal artifact reduction using cycle-consistent adversarial network for intensity-modulated head and neck radiation therapy treatment planning.

PURPOSE: To develop a deep learning-based metal artifact reduction (DL-MAR) method using unpaired da...

System for High-Intensity Evaluation During Radiation Therapy (SHIELD-RT): A Prospective Randomized Study of Machine Learning-Directed Clinical Evaluations During Radiation and Chemoradiation.

PURPOSE: Patients undergoing outpatient radiotherapy (RT) or chemoradiation (CRT) frequently require...

Use of artificial intelligence in computed tomography dose optimisation.

The field of artificial intelligence (AI) is transforming almost every aspect of modern society, inc...

Deep Learning in Radiation Oncology Treatment Planning for Prostate Cancer: A Systematic Review.

Radiation oncology for prostate cancer is important as it can decrease the morbidity and mortality a...

Fully-Connected Neural Networks with Reduced Parameterization for Predicting Histological Types of Lung Cancer from Somatic Mutations.

Several challenges appear in the application of deep learning to genomic data. First, the dimensiona...

Knowledge Models as Teaching Aid for Training Intensity Modulated Radiation Therapy Planning: A Lung Cancer Case Study.

Artificial intelligence (AI) employs knowledge models that often behave as a black-box to the major...

Artificial intelligence and soft skills in radiation oncology: Data versus wisdom.

Artificial intelligence in radiation oncology.

Artificial intelligence (AI) has the potential to fundamentally alter the way medicine is practised....

Development and Cross-Validation of a Nomogram for Chronic Kidney Disease Following Robot-Assisted Radical Cystectomy.

We sought to identify the factors associated with deterioration of renal functions after robot-assi...

The deep learning model combining CT image and clinicopathological information for predicting ALK fusion status and response to ALK-TKI therapy in non-small cell lung cancer patients.

PURPOSE: This study aimed to investigate the deep learning model (DLM) combining computed tomography...

Technical Note: Deep Learning approach for automatic detection and identification of patient positioning devices for radiation therapy.

PURPOSE: Automatic detection and identification of setup devices, using a deep convolutional neural ...

Identifying sarcopenia in advanced non-small cell lung cancer patients using skeletal muscle CT radiomics and machine learning.

BACKGROUND: Sarcopenia has been confirmed as a poor prognostic indicator of lung cancer. However, th...

A knowledge-based intensity-modulated radiation therapy treatment planning technique for locally advanced nasopharyngeal carcinoma radiotherapy.

BACKGROUND: To investigate the feasibility of a knowledge-based automated intensity-modulated radiat...

Using deep learning to predict beam-tunable Pareto optimal dose distribution for intensity-modulated radiation therapy.

PURPOSE: Many researchers have developed deep learning models for predicting clinical dose distribut...

Development of prognostic model for patients at CKD stage 3a and 3b in South Central China using computational intelligence.

BACKGROUND: Chronic kidney disease (CKD) stage 3 was divided into two subgroups by eGFR (45 mL/ min ...