AIMC Topic: Neoplasm Staging
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Development and validation of a real-time artificial intelligence-assisted system for detecting early gastric cancer: A multicentre retrospective diagnostic study.
EBioMedicine
Nov 27, 2020
BACKGROUND: We aimed to develop and validate a real-time deep convolutional neural networks (DCNNs) system for detecting early gastric cancer (EGC).
Comparing Laparotomy with Robot-assisted Interval Debulking Surgery for Patients with Advanced Epithelial Ovarian Cancer Receiving Neoadjuvant Chemotherapy.
Journal of minimally invasive gynecology
Nov 26, 2020
STUDY OBJECTIVE: Compare survival of patients with advanced epithelial ovarian cancer (EOC) undergoing interval debulking surgery (IDS) with either robot-assisted (R-IDS) or open (O-IDS) approach. Second, we assessed the impact of adjuvant and neoadj...
Using Machine Learning Algorithms to Predict Immunotherapy Response in Patients with Advanced Melanoma.
Clinical cancer research : an official journal of the American Association for Cancer Research
Nov 18, 2020
PURPOSE: Several biomarkers of response to immune checkpoint inhibitors (ICI) show potential but are not yet scalable to the clinic. We developed a pipeline that integrates deep learning on histology specimens with clinical data to predict ICI respon...
Skin Neoplasms
Humans
Aged
Follow-Up Studies
Neoplasm Staging
Adult
Machine Learning
Risk Assessment
Skin
Male
Prospective Studies
Disease Progression
Progression-Free Survival
Middle Aged
Prognosis
ROC Curve
Drug Resistance, Neoplasm
Female
Immune Checkpoint Inhibitors
Melanoma
Image Processing, Computer-Assisted
Artificial Intelligence for Response Evaluation With PET/CT.
Seminars in nuclear medicine
Nov 11, 2020
Positron emission tomography (PET)/computed tomography (CT) are nuclear diagnostic imaging modalities that are routinely deployed for cancer staging and monitoring. They hold the advantage of detecting disease related biochemical and physiologic abno...
Machine Learning-Guided Adjuvant Treatment of Head and Neck Cancer.
JAMA network open
Nov 2, 2020
IMPORTANCE: Postoperative chemoradiation is the standard of care for cancers with positive margins or extracapsular extension, but the benefit of chemotherapy is unclear for patients with other intermediate risk features.
Neural Networks, Computer
Machine Learning
Retrospective Studies
Female
Aged
Humans
Patient Selection
Tumor Burden
Chemoradiotherapy, Adjuvant
Proportional Hazards Models
Lymph Nodes
Radiotherapy, Adjuvant
Squamous Cell Carcinoma of Head and Neck
Neoplasm Staging
Laryngeal Neoplasms
Neoplasm Grading
Mouth Neoplasms
Otorhinolaryngologic Surgical Procedures
Oropharyngeal Neoplasms
Male
Hypopharyngeal Neoplasms
Deep Learning
Cohort Studies
Logistic Models
The role of artificial intelligence to quantify the tumour-stroma ratio for survival in colorectal cancer.
EBioMedicine
Oct 21, 2020
Machine learning-based prediction of microsatellite instability and high tumor mutation burden from contrast-enhanced computed tomography in endometrial cancers.
Scientific reports
Oct 20, 2020
To evaluate whether radiomic features from contrast-enhanced computed tomography (CE-CT) can identify DNA mismatch repair deficient (MMR-D) and/or tumor mutational burden-high (TMB-H) endometrial cancers (ECs). Patients who underwent targeted massive...
Humans
Machine Learning
DNA Mismatch Repair
Computer Simulation
DNA Polymerase II
Prognosis
Middle Aged
Poly-ADP-Ribose Binding Proteins
Cohort Studies
Tomography, X-Ray Computed
Mutation
Uterus
Female
Tumor Suppressor Protein p53
Neoplasm Staging
Aged
Endometrial Neoplasms
Microsatellite Instability
Carcinoma, Endometrioid
Deep learning for elective neck delineation: More consistent and time efficient.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Oct 14, 2020
BACKGROUND/PURPOSE: Delineation of the lymph node levels of the neck for irradiation of the elective clinical target volume in head and neck cancer (HNC) patients is time consuming and prone to interobserver variability (IOV), although international ...
Artificial intelligence quantified tumour-stroma ratio is an independent predictor for overall survival in resectable colorectal cancer.
EBioMedicine
Oct 8, 2020
BACKGROUND: An artificial intelligence method could accelerate the clinical implementation of tumour-stroma ratio (TSR), which has prognostic relevance in colorectal cancer (CRC). We, therefore, developed a deep learning model for the fully automated...
Using machine learning to create prognostic systems for endometrial cancer.
Gynecologic oncology
Oct 2, 2020
OBJECTIVE: We used a novel machine learning algorithm to develop a precision prognostication system for endometrial cancer.
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