Machine Learning In Clinical Neuroimaging

Author : Ahmed Abdulkadir,Deepti R. Bathula,Nicha C. Dvornek,Sindhuja T. Govindarajan,Mohamad Habes,Vinod Kumar,Esten Leonardsen,Thomas Wolfers,Yiming Xiao
Publisher : Springer Nature
Page : 183 pages
File Size : 40,7 Mb
Release : 2023-10-07
Category : Computers
ISBN : 9783031448584

Get Book

Machine Learning in Clinical Neuroimaging by Ahmed Abdulkadir,Deepti R. Bathula,Nicha C. Dvornek,Sindhuja T. Govindarajan,Mohamad Habes,Vinod Kumar,Esten Leonardsen,Thomas Wolfers,Yiming Xiao Pdf

This book constitutes the refereed proceedings of the 6th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2023, held in Conjunction with MICCAI 2023 in Vancouver, Canada, in October 2023. The book includes 16 papers which were carefully reviewed and selected from 28 full-length submissions. The 6th International Workshop on Machine Learning in Clinical Neuroimaging (MLCN 2023) aims to bring together the top researchers in both machine learning and clinical neuroscience as well as tech-savvy clinicians to address two main challenges: 1) development of methodological approaches for analyzing complex and heterogeneous neuroimaging data (machine learning track); and 2) filling the translational gap in applying existing machine learning methods in clinical practices (clinical neuroimaging track). The papers are categorzied into topical sub-headings on Machine Learning and Clinical Applications.

Author : Ahmed Abdulkadir,Deepti R. Bathula,Nicha C. Dvornek,Mohamad Habes,Seyed Mostafa Kia,Vinod Kumar,Thomas Wolfers
Publisher : Springer Nature
Page : 190 pages
File Size : 47,7 Mb
Release : 2022-10-07
Category : Computers
ISBN : 9783031178993

Get Book

Machine Learning in Clinical Neuroimaging by Ahmed Abdulkadir,Deepti R. Bathula,Nicha C. Dvornek,Mohamad Habes,Seyed Mostafa Kia,Vinod Kumar,Thomas Wolfers Pdf

This book constitutes the refereed proceedings of the 5th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2022, held in Conjunction with MICCAI 2022, Singapore in September 2022. The book includes 17 papers which were carefully reviewed and selected from 23 full-length submissions. The 5th international workshop on Machine Learning in Clinical Neuroimaging (MLCN2022) aims to bring together the top researchers in both machine learning and clinical neuroscience as well as tech-savvy clinicians to address two main challenges: 1) development of methodological approaches for analyzing complex and heterogeneous neuroimaging data (machine learning track); and 2) filling the translational gap in applying existing machine learning methods in clinical practices (clinical neuroimaging track). The papers are categorzied into topical sub-headings: Morphometry; Diagnostics, and Aging, and Neurodegeneration.

Author : Ahmed Abdulkadir,Seyed Mostafa Kia,Mohamad Habes,Vinod Kumar,Jane Maryam Rondina,Chantal Tax,Thomas Wolfers
Publisher : Springer Nature
Page : 185 pages
File Size : 48,8 Mb
Release : 2021-09-22
Category : Computers
ISBN : 9783030875862

Get Book

Machine Learning in Clinical Neuroimaging by Ahmed Abdulkadir,Seyed Mostafa Kia,Mohamad Habes,Vinod Kumar,Jane Maryam Rondina,Chantal Tax,Thomas Wolfers Pdf

This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2021, held on September 27, 2021, in conjunction with MICCAI 2021. The workshop was held virtually due to the COVID-19 pandemic. The 17 papers presented in this book were carefully reviewed and selected from 27 submissions. They were organized in topical sections named: computational anatomy and brain networks and time series.

Author : Seyed Mostafa Kia,Hassan Mohy-ud-Din,Ahmed Abdulkadir,Cher Bass,Mohamad Habes,Jane Maryam Rondina,Chantal Tax,Hongzhi Wang,Thomas Wolfers,Saima Rathore,Madhura Ingalhalikar
Publisher : Springer Nature
Page : 319 pages
File Size : 54,5 Mb
Release : 2020-12-30
Category : Computers
ISBN : 9783030668433

Get Book

Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology by Seyed Mostafa Kia,Hassan Mohy-ud-Din,Ahmed Abdulkadir,Cher Bass,Mohamad Habes,Jane Maryam Rondina,Chantal Tax,Hongzhi Wang,Thomas Wolfers,Saima Rathore,Madhura Ingalhalikar Pdf

This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2020, and the Second International Workshop on Radiogenomics in Neuro-oncology, RNO-AI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020.* For MLCN 2020, 18 papers out of 28 submissions were accepted for publication. The accepted papers present novel contributions in both developing new machine learning methods and applications of existing methods to solve challenging problems in clinical neuroimaging. For RNO-AI 2020, all 8 submissions were accepted for publication. They focus on addressing the problems of applying machine learning to large and multi-site clinical neuroimaging datasets. The workshop aimed to bring together experts in both machine learning and clinical neuroimaging to discuss and hopefully bridge the existing challenges of applied machine learning in clinical neuroscience. *The workshops were held virtually due to the COVID-19 pandemic.

Author : Victor E. Staartjes,Luca Regli,Carlo Serra
Publisher : Springer Nature
Page : 343 pages
File Size : 45,7 Mb
Release : 2021-12-03
Category : Medical
ISBN : 9783030852924

Get Book

Machine Learning in Clinical Neuroscience by Victor E. Staartjes,Luca Regli,Carlo Serra Pdf

This book bridges the gap between data scientists and clinicians by introducing all relevant aspects of machine learning in an accessible way, and will certainly foster new and serendipitous applications of machine learning in the clinical neurosciences. Building from the ground up by communicating the foundational knowledge and intuitions first before progressing to more advanced and specific topics, the book is well-suited even for clinicians without prior machine learning experience. Authored by a wide array of experienced global machine learning groups, the book is aimed at clinicians who are interested in mastering the basics of machine learning and who wish to get started with their own machine learning research. The volume is structured in two major parts: The first uniquely introduces all major concepts in clinical machine learning from the ground up, and includes step-by-step instructions on how to correctly develop and validate clinical prediction models. It also includes methodological and conceptual foundations of other applications of machine learning in clinical neuroscience, such as applications of machine learning to neuroimaging, natural language processing, and time series analysis. The second part provides an overview of some state-of-the-art applications of these methodologies. The Machine Intelligence in Clinical Neuroscience (MICN) Laboratory at the Department of Neurosurgery of the University Hospital Zurich studies clinical applications of machine intelligence to improve patient care in clinical neuroscience. The group focuses on diagnostic, prognostic and predictive analytics that aid in decision-making by increasing objectivity and transparency to patients. Other major interests of our group members are in medical imaging, and intraoperative applications of machine vision.

Author : Reza Forghani
Publisher : Elsevier Health Sciences
Page : 192 pages
File Size : 49,9 Mb
Release : 2020-10-23
Category : Medical
ISBN : 9780323712453

Get Book

Machine Learning and Other Artificial Intelligence Applications, An Issue of Neuroimaging Clinics of North America, E-Book by Reza Forghani Pdf

This issue of Neuroimaging Clinics of North America focuses on Artificial Intelligence and Machine Learning and is edited by Dr. Reza Forghani. Articles will include: A Brief History of Artificial Intelligence; Evolution of Approaches for Computerized Image Analysis; Overview of Machine Learning Part 1: Classic Approaches; Overview of Machine Learning Part 2: Artificial Neural Networks & Deep Learning; Overview of Natural Language Processing; Artificial Intelligence & Stroke Imaging: An East Coast Perspective; Artificial Intelligence & Stroke Imaging: A West Coast Perspective; Artificial Intelligence Applications for Brain Tumor Imaging; Diverse Applications of Artificial Intelligence in Neuroradiology; Artificial Intelligence Applications for Head and Neck Imaging; Artificial Intelligence Applications for Predictive Analytics and Workflow Optimization; Artificial Intelligence, Advanced Visualization, and 3D Printing; Ethical & Legal Considerations for Artificial Intelligence; Comprehensive (or 360) Artificial Intelligence: Beyond Image Interpretation Alone, and more!

Author : Ahmed Abdulkadir,Seyed Mostafa Kia,Mohamad Habes,Vinod Kumar,Jane Maryam Rondina,Chantal Tax,Thomas Wolfers
Publisher : Unknown
Page : 0 pages
File Size : 44,8 Mb
Release : 2021
Category : Electronic
ISBN : 3030875873

Get Book

Machine Learning in Clinical Neuroimaging by Ahmed Abdulkadir,Seyed Mostafa Kia,Mohamad Habes,Vinod Kumar,Jane Maryam Rondina,Chantal Tax,Thomas Wolfers Pdf

This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2021, held on September 27, 2021, in conjunction with MICCAI 2021. The workshop was held virtually due to the COVID-19 pandemic. The 17 papers presented in this book were carefully reviewed and selected from 27 submissions. They were organized in topical sections named: computational anatomy and brain networks and time series.

Author : Luping Zhou,Duygu Sarikaya,Seyed Mostafa Kia,Stefanie Speidel,Anand Malpani,Daniel Hashimoto,Mohamad Habes,Tommy Löfstedt,Kerstin Ritter,Hongzhi Wang
Publisher : Springer Nature
Page : 114 pages
File Size : 54,6 Mb
Release : 2019-10-10
Category : Computers
ISBN : 9783030326951

Get Book

OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging by Luping Zhou,Duygu Sarikaya,Seyed Mostafa Kia,Stefanie Speidel,Anand Malpani,Daniel Hashimoto,Mohamad Habes,Tommy Löfstedt,Kerstin Ritter,Hongzhi Wang Pdf

This book constitutes the refereed proceedings of the Second International Workshop on Context-Aware Surgical Theaters, OR 2.0 2019, and the Second International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. For OR 2.0 all 6 submissions were accepted for publication. They aim to highlight the potential use of machine vision and perception, robotics, surgical simulation and modeling, multi-modal data fusion and visualization, image analysis, advanced imaging, advanced display technologies, human-computer interfaces, sensors, wearable and implantable electronics and robots, visual attention models, cognitive models, decision support networks to enhance surgical procedural assistance, context-awareness and team communication in the operating theater, human-robot collaborative systems, and surgical training and assessment. MLCN 2019 accepted 6 papers out of 7 submissions for publication. They focus on addressing the problems of applying machine learning to large and multi-site clinical neuroimaging datasets. The workshop aimed to bring together experts in both machine learning and clinical neuroimaging to discuss and hopefully bridge the existing challenges of applied machine learning in clinical neuroscience.

Author : Ahmed Abdulkadir,Deepti R. Bathula,Nicha C. Dvornek,Mohamad Habes,Seyed Mostafa Kia,Vinod Kumar,Thomas Wolfers
Publisher : Unknown
Page : 0 pages
File Size : 47,9 Mb
Release : 2022
Category : Diagnostic imaging
ISBN : 8303117890

Get Book

Machine Learning in Clinical Neuroimaging by Ahmed Abdulkadir,Deepti R. Bathula,Nicha C. Dvornek,Mohamad Habes,Seyed Mostafa Kia,Vinod Kumar,Thomas Wolfers Pdf

This book constitutes the refereed proceedings of the 5th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2022, held in Conjunction with MICCAI 2022, Singapore in September 2022. The book includes 17 papers which were carefully reviewed and selected from 23 full-length submissions. The 5th international workshop on Machine Learning in Clinical Neuroimaging (MLCN2022) aims to bring together the top researchers in both machine learning and clinical neuroscience as well as tech-savvy clinicians to address two main challenges: 1) development of methodological approaches for analyzing complex and heterogeneous neuroimaging data (machine learning track); and 2) filling the translational gap in applying existing machine learning methods in clinical practices (clinical neuroimaging track). The papers are categorzied into topical sub-headings: Morphometry; Diagnostics, and Aging, and Neurodegeneration. .

Author : Anitha S. Pillai,Bindu Menon
Publisher : CRC Press
Page : 133 pages
File Size : 41,7 Mb
Release : 2024-02-15
Category : Computers
ISBN : 9781003815549

Get Book

Machine Learning and Deep Learning in Neuroimaging Data Analysis by Anitha S. Pillai,Bindu Menon Pdf

Machine learning (ML) and deep learning (DL) have become essential tools in healthcare. They are capable of processing enormous amounts of data to find patterns and are also adopted into methods that manage and make sense of healthcare data, either electronic healthcare records or medical imagery. This book explores how ML/DL can assist neurologists in identifying, classifying or predicting neurological problems that require neuroimaging. With the ability to model high-dimensional datasets, supervised learning algorithms can help in relating brain images to behavioral or clinical observations and unsupervised learning can uncover hidden structures/patterns in images. Bringing together artificial intelligence (AI) experts as well as medical practitioners, these chapters cover the majority of neuro problems that use neuroimaging for diagnosis, along with case studies and directions for future research.

Author : Nianyin Zeng,Siyang Zuo,Guoyan Zheng,Yangming Ou,Tong Tong
Publisher : Frontiers Media SA
Page : 224 pages
File Size : 55,9 Mb
Release : 2020-07-03
Category : Electronic
ISBN : 9782889638260

Get Book

Artificial Intelligence for Medical Image Analysis of NeuroImaging Data by Nianyin Zeng,Siyang Zuo,Guoyan Zheng,Yangming Ou,Tong Tong Pdf

Author : Danail Stoyanov,Zeike Taylor,Seyed Mostafa Kia,Ipek Oguz,Mauricio Reyes,Anne Martel,Lena Maier-Hein,Andre F. Marquand,Edouard Duchesnay,Tommy Löfstedt,Bennett Landman,M. Jorge Cardoso,Carlos A. Silva,Sergio Pereira,Raphael Meier
Publisher : Springer
Page : 149 pages
File Size : 43,6 Mb
Release : 2018-10-23
Category : Computers
ISBN : 9783030026288

Get Book

Understanding and Interpreting Machine Learning in Medical Image Computing Applications by Danail Stoyanov,Zeike Taylor,Seyed Mostafa Kia,Ipek Oguz,Mauricio Reyes,Anne Martel,Lena Maier-Hein,Andre F. Marquand,Edouard Duchesnay,Tommy Löfstedt,Bennett Landman,M. Jorge Cardoso,Carlos A. Silva,Sergio Pereira,Raphael Meier Pdf

This book constitutes the refereed joint proceedings of the First International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2018, the First International Workshop on Deep Learning Fails, DLF 2018, and the First International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 4 full MLCN papers, the 6 full DLF papers, and the 6 full iMIMIC papers included in this volume were carefully reviewed and selected. The MLCN contributions develop state-of-the-art machine learning methods such as spatio-temporal Gaussian process analysis, stochastic variational inference, and deep learning for applications in Alzheimer's disease diagnosis and multi-site neuroimaging data analysis; the DLF papers evaluate the strengths and weaknesses of DL and identify the main challenges in the current state of the art and future directions; the iMIMIC papers cover a large range of topics in the field of interpretability of machine learning in the context of medical image analysis.

Author : Andrea Mechelli,Sandra Vieira
Publisher : Academic Press
Page : 412 pages
File Size : 47,6 Mb
Release : 2019-11-14
Category : Medical
ISBN : 9780128157404

Get Book

Machine Learning by Andrea Mechelli,Sandra Vieira Pdf

Machine Learning is an area of artificial intelligence involving the development of algorithms to discover trends and patterns in existing data; this information can then be used to make predictions on new data. A growing number of researchers and clinicians are using machine learning methods to develop and validate tools for assisting the diagnosis and treatment of patients with brain disorders. Machine Learning: Methods and Applications to Brain Disorders provides an up-to-date overview of how these methods can be applied to brain disorders, including both psychiatric and neurological disease. This book is written for a non-technical audience, such as neuroscientists, psychologists, psychiatrists, neurologists and health care practitioners. Provides a non-technical introduction to machine learning and applications to brain disorders Includes a detailed description of the most commonly used machine learning algorithms as well as some novel and promising approaches Covers the main methodological challenges in the application of machine learning to brain disorders Provides a step-by-step tutorial for implementing a machine learning pipeline to neuroimaging data in Python

Author : Irina Rish,Georg Langs,Leila Wehbe,Guillermo Cecchi,Kai-min Kevin Chang,Brian Murphy
Publisher : Springer
Page : 129 pages
File Size : 48,5 Mb
Release : 2016-09-12
Category : Computers
ISBN : 9783319451749

Get Book

Machine Learning and Interpretation in Neuroimaging by Irina Rish,Georg Langs,Leila Wehbe,Guillermo Cecchi,Kai-min Kevin Chang,Brian Murphy Pdf

This book constitutes the revised selected papers from the 4th International Workshop on Machine Learning and Interpretation in Neuroimaging, MLINI 2014, held in Montreal, QC, Canada, in December 2014 as a satellite event of the 11th annual conference on Neural Information Processing Systems, NIPS 2014. The 10 MLINI 2014 papers presented in this volume were carefully reviewed and selected from 17 submissions. They were organized in topical sections named: networks and decoding; speech; clinics and cognition; and causality and time-series. In addition, the book contains the 3 best papers presented at MLINI 2013.

Author : Olivier Colliot
Publisher : Springer Nature
Page : 1058 pages
File Size : 40,8 Mb
Release : 2023-07-24
Category : Medical
ISBN : 9781071631959

Get Book

Machine Learning for Brain Disorders by Olivier Colliot Pdf

This Open Access volume provides readers with an up-to-date and comprehensive guide to both methodological and applicative aspects of machine learning (ML) for brain disorders. The chapters in this book are organized into five parts. Part One presents the fundamentals of ML. Part Two looks at the main types of data used to characterize brain disorders, including clinical assessments, neuroimaging, electro- and magnetoencephalography, genetics and omics data, electronic health records, mobile devices, connected objects and sensors. Part Three covers the core methodologies of ML in brain disorders and the latest techniques used to study them. Part Four is dedicated to validation and datasets, and Part Five discusses applications of ML to various neurological and psychiatric disorders. In the Neuromethods series style, chapters include the kind of detail and key advice from the specialists needed to get successful results in your laboratory. Comprehensive and cutting, Machine Learning for Brain Disorders is a valuable resource for researchers and graduate students who are new to this field, as well as experienced researchers who would like to further expand their knowledge in this area. This book will be useful to students and researchers from various backgrounds such as engineers, computer scientists, neurologists, psychiatrists, radiologists, and neuroscientists.