Easy-to-use machine learning system for the prediction of IDH mutation and 1p/19q codeletion using MRI images of adult-type diffuse gliomas

[1]  L. Rundo,et al.  Convolutional Neural Network Techniques for Brain Tumor Classification (from 2015 to 2022): Review, Challenges, and Future Perspectives , 2022, Diagnostics.

[2]  M. J. van den Bent,et al.  Combined molecular subtyping, grading, and segmentation of glioma using multi-task deep learning , 2022, Neuro-oncology.

[3]  I. Florian,et al.  External Validation of a Convolutional Neural Network for IDH Mutation Prediction , 2022, Medicina.

[4]  Khalid Twarish Alhamazani,et al.  Implementation of Machine Learning Models for the Prevention of Kidney Diseases (CKD) or Their Derivatives , 2021, Comput. Intell. Neurosci..

[5]  I. Byon,et al.  Establishment of a prediction tool for ocular trauma patients with machine learning algorithm , 2021, International Journal of Ophthalmology.

[6]  G. Reifenberger,et al.  The 2021 WHO Classification of Tumors of the Central Nervous System: a summary. , 2021, Neuro-oncology.

[7]  S. Miyamoto,et al.  Prognostic stratification for IDH-wild-type lower-grade astrocytoma by Sanger sequencing and copy-number alteration analysis with MLPA , 2021, Scientific Reports.

[8]  Seok-Gu Kang,et al.  Fully Automated Hybrid Approach to Predict the IDH Mutation Status of Gliomas via Deep Learning and Radiomics. , 2020, Neuro-oncology.

[9]  K. Masamune,et al.  Prediction of lower-grade glioma molecular subtypes using deep learning , 2019, Journal of Neuro-Oncology.

[10]  T. Yanagisawa,et al.  Prediction of IDH and TERT promoter mutations in low-grade glioma from magnetic resonance images using a convolutional neural network , 2019, Scientific Reports.

[11]  Sahil Nalawade,et al.  Classification of brain tumor isocitrate dehydrogenase status using MRI and deep learning , 2019, Journal of medical imaging.

[12]  S. Hyun,et al.  Development of Predictive Models in Patients with Epiphora Using Lacrimal Scintigraphy and Machine Learning , 2019, Nuclear Medicine and Molecular Imaging.

[13]  Hee Jun Choi,et al.  A predictive model for high/low risk group according to oncotype DX recurrence score using machine learning. , 2019, European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology.

[14]  Armando J Lorenzo,et al.  Predictive Analytics and Modeling Employing Machine Learning Technology: The Next Step in Data Sharing, Analysis, and Individualized Counseling Explored With a Large, Prospective Prenatal Hydronephrosis Database. , 2019, Urology.

[15]  D. Cahill,et al.  The prognostic value of maximal surgical resection is attenuated in oligodendroglioma subgroups of adult diffuse glioma: a multicenter retrospective study , 2018, Journal of Neuro-Oncology.

[16]  P. Baldi,et al.  Deep-Learning Convolutional Neural Networks Accurately Classify Genetic Mutations in Gliomas , 2018, American Journal of Neuroradiology.

[17]  Hideo Nakamura,et al.  Prognostic relevance of genetic alterations in diffuse lower-grade gliomas , 2018, Neuro-oncology.

[18]  Raymond Y Huang,et al.  Residual Convolutional Neural Network for the Determination of IDH Status in Low- and High-Grade Gliomas from MR Imaging , 2017, Clinical Cancer Research.

[19]  M. J. van den Bent,et al.  The impact of surgery in molecularly defined low-grade glioma: an integrated clinical, radiological, and molecular analysis , 2017, Neuro-oncology.

[20]  Steven J. M. Jones,et al.  Comprehensive, Integrative Genomic Analysis of Diffuse Lower-Grade Gliomas. , 2015, The New England journal of medicine.

[21]  Satoru Miyano,et al.  Mutational landscape and clonal architecture in grade II and III gliomas , 2015, Nature Genetics.

[22]  Y. Kanda,et al.  Investigation of the freely available easy-to-use software ‘EZR' for medical statistics , 2012, Bone Marrow Transplantation.

[23]  P. Wesseling,et al.  Multiplex ligation-dependent probe amplification: a diagnostic tool for simultaneous identification of different genetic markers in glial tumors. , 2006, The Journal of molecular diagnostics : JMD.

[24]  Stanisław Supplitt,et al.  Machine-learning-based Analysis Identifies miRNA Expression Profile for Diagnosis and Prediction of Colorectal Cancer: A Preliminary Study , 2022, Cancer Genomics & Proteomics.