Oncology/Hematology

Lung Cancer

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

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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...

Aug 2020 32862251
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...

Aug 2020 32872133
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...

Aug 2020 33733183
Artificial intelligence in radiation oncology.

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

Aug 2020 32843739
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...

Aug 2020 32631086
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...

Aug 2020 32767522
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...

Aug 2020 32746873
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...

Aug 2020 32621789
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 ...

Aug 2020 32740698
Synergistic drug combinations and machine learning for drug repurposing in chordoma.

Chordoma is a devastating rare cancer that affects one in a million people. With a mean-survival of ...

Jul 2020 32737414
Deep learning-based image analysis methods for brightfield-acquired multiplex immunohistochemistry images.

BACKGROUND: Multiplex immunohistochemistry (mIHC) permits the labeling of six or more distinct cell ...

Jul 2020 32723384
Radiogenomics for predicting p53 status, PD-L1 expression, and prognosis with machine learning in pancreatic cancer.

BACKGROUND: Radiogenomics is an emerging field that integrates "Radiomics" and "Genomics". In the cu...

Jul 2020 32690867
Reinventing radiation therapy with machine learning and imaging bio-markers (radiomics): State-of-the-art, challenges and perspectives.

Radiation therapy is a pivotal cancer treatment that has significantly progressed over the last deca...

Jul 2020 32697964
Machine learning of serum metabolic patterns encodes early-stage lung adenocarcinoma.

Early cancer detection greatly increases the chances for successful treatment, but available diagnos...

Jul 2020 32678093
Predicting respiratory failure after pulmonary lobectomy using machine learning techniques.

BACKGROUND: When pulmonary complications occur, postlobectomy patients have a higher mortality rate,...

Jul 2020 32680748
Radiomics in radiation oncology-basics, methods, and limitations.

Over the past years, the quantity and complexity of imaging data available for the clinical manageme...

Jul 2020 32647917
Molecular docking and machine learning analysis of Abemaciclib in colon cancer.

BACKGROUND: The main challenge in cancer research is the identification of different omic variables ...

Jul 2020 32640984
Histological Subtypes Classification of Lung Cancers on CT Images Using 3D Deep Learning and Radiomics.

RATIONALE AND OBJECTIVES: Histological subtypes of lung cancers are critical for clinical treatment ...

Jul 2020 32622740
Artificial intelligence for the detection of esophageal and esophagogastric junctional adenocarcinoma.

BACKGROUND AND AIM: Conventional endoscopy for the early detection of esophageal and esophagogastric...

Jun 2020 32511793
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