Machine Learning and Deep Learning Applications in Multiple Myeloma Diagnosis, Prognosis, and Treatment Selection
出版年份 2022 全文链接
标题
Machine Learning and Deep Learning Applications in Multiple Myeloma Diagnosis, Prognosis, and Treatment Selection
作者
关键词
-
出版物
Cancers
Volume 14, Issue 3, Pages 606
出版商
MDPI AG
发表日期
2022-01-26
DOI
10.3390/cancers14030606
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- A review of deep learning applications for genomic selection
- (2021) Osval Antonio Montesinos-López et al. BMC GENOMICS
- Potential Role of microRNAs in inducing Drug Resistance in Patients with Multiple Myeloma
- (2021) Alessandro Allegra et al. Cells
- Differentiating Between Multiple Myeloma and Metastasis Subtypes of Lumbar Vertebra Lesions Using Machine Learning–Based Radiomics
- (2021) Xing Xiong et al. Frontiers in Oncology
- Survival prediction and treatment optimization of multiple myeloma patients using machine-learning models based on clinical and gene expression data
- (2021) Adrián Mosquera Orgueira et al. LEUKEMIA
- Improved 18-FDG PET/CT diagnosis of multiple myeloma diffuse disease by radiomics analysis
- (2021) Charles Mesguich et al. NUCLEAR MEDICINE COMMUNICATIONS
- Diagnosis and staging of multiple myelomausing serum-based laser-induced breakdownspectroscopy combined with machinelearning methods
- (2021) Xue Chen et al. Biomedical Optics Express
- Employment of Artificial Intelligence Based on Routine Laboratory Results for the Early Diagnosis of Multiple Myeloma
- (2021) Wei Yan et al. Frontiers in Oncology
- Machine Learning Applicability for Classification of PAD/VCD Chemotherapy Response Using 53 Multiple Myeloma RNA Sequencing Profiles
- (2021) Nicolas Borisov et al. Frontiers in Oncology
- Outcome data from >10 000 multiple myeloma patients in the Danish and Swedish national registries
- (2021) Cecilie Hveding Blimark et al. EUROPEAN JOURNAL OF HAEMATOLOGY
- Epidemiology, genetics and treatment of multiple myeloma and precursor diseases
- (2021) Kari Hemminki et al. INTERNATIONAL JOURNAL OF CANCER
- Machine learning predicts treatment sensitivity in multiple myeloma based on molecular and clinical information coupled with drug response
- (2021) Lucas Venezian Povoa et al. PLoS One
- AI-supported modified risk staging for multiple myeloma cancer useful in real-world scenario
- (2021) Akanksha Farswan et al. Translational Oncology
- Integrative Analysis of Gene Expression Through One-Class Logistic Regression Machine Learning Identifies Stemness Features in Multiple Myeloma
- (2021) Chunmei Ban et al. Frontiers in Genetics
- Reinforcement Learning for Precision Oncology
- (2021) Jan-Niklas Eckardt et al. Cancers
- Accurate classification of plasma cell dyscrasias is achieved by combining artificial intelligence and flow cytometry
- (2021) Valentin Clichet et al. BRITISH JOURNAL OF HAEMATOLOGY
- Deep Learning in Cancer Diagnosis and Prognosis Prediction: A Minireview on Challenges, Recent Trends, and Future Directions
- (2021) Ahsan Bin Tufail et al. Computational and Mathematical Methods in Medicine
- Deep learning in cancer diagnosis, prognosis and treatment selection
- (2021) Khoa A. Tran et al. Genome Medicine
- Human, All Too Human? An All-Around Appraisal of the “Artificial Intelligence Revolution” in Medical Imaging
- (2021) Francesca Coppola et al. Frontiers in Psychology
- Deep profiling of apoptotic pathways with mass cytometry identifies a synergistic drug combination for killing myeloma cells
- (2020) Charis E. Teh et al. CELL DEATH AND DIFFERENTIATION
- Latest treatment strategies aiming for a cure in transplant-eligible multiple myeloma patients: how I cure younger MM patients with lower cost
- (2020) Kenshi Suzuki INTERNATIONAL JOURNAL OF HEMATOLOGY
- Discrimination of infiltrative glioma boundary based on laser-induced breakdown spectroscopy
- (2020) Geer Teng et al. SPECTROCHIMICA ACTA PART B-ATOMIC SPECTROSCOPY
- Artificial intelligence: radiologists’ expectations and opinions gleaned from a nationwide online survey
- (2020) Francesca Coppola et al. Radiologia Medica
- A “Third Wheel” Effect in Health Decision Making Involving Artificial Entities: A Psychological Perspective
- (2020) Stefano Triberti et al. Frontiers in Public Health
- Integrating spatial gene expression and breast tumour morphology via deep learning
- (2020) Bryan He et al. Nature Biomedical Engineering
- Gene Networks Constructed Through Simulated Treatment Learning can Predict Proteasome Inhibitor Benefit in Multiple Myeloma
- (2020) Joske Ubels et al. CLINICAL CANCER RESEARCH
- A historical perspective of explainable Artificial Intelligence
- (2020) Roberto Confalonieri et al. Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery
- Machine-based detection and classification for bone marrow aspirate differential counts: initial development focusing on nonneoplastic cells
- (2019) Ramraj Chandradevan et al. LABORATORY INVESTIGATION
- Artificial Intelligence in Imaging: The Radiologist’s Role
- (2019) Daniel L. Rubin Journal of the American College of Radiology
- Potential Liability for Physicians Using Artificial Intelligence
- (2019) W. Nicholson Price et al. JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION
- The relative importance of factors predicting outcome for myeloma patients at different ages: results from 3894 patients in the Myeloma XI trial
- (2019) Charlotte Pawlyn et al. LEUKEMIA
- Deep learning for drug response prediction in cancer
- (2019) Delora Baptista et al. BRIEFINGS IN BIOINFORMATICS
- Automated Whole-Body Bone Lesion Detection for Multiple Myeloma on 68Ga-Pentixafor PET/CT Imaging Using Deep Learning Methods
- (2018) Lina Xu et al. Contrast Media & Molecular Imaging
- Big Data and Machine Learning in Health Care
- (2018) Andrew L. Beam et al. JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION
- Immunoproteasome-selective and non-selective inhibitors: A promising approach for the treatment of multiple myeloma
- (2018) Roberta Ettari et al. PHARMACOLOGY & THERAPEUTICS
- Myeloma: Patient accounts of their pathways to diagnosis
- (2018) Debra A. Howell et al. PLoS One
- Diagnosis of human malignancies using laser-induced breakdown spectroscopy in combination with chemometric methods
- (2018) Xue Chen et al. SPECTROCHIMICA ACTA PART B-ATOMIC SPECTROSCOPY
- Using LIBS to diagnose melanoma in biomedical fluids deposited on solid substrates: Limits of direct spectral analysis and capability of machine learning
- (2018) Rosalba Gaudiuso et al. SPECTROCHIMICA ACTA PART B-ATOMIC SPECTROSCOPY
- Demystification of AI-driven medical image interpretation: past, present and future
- (2018) Peter Savadjiev et al. EUROPEAN RADIOLOGY
- Deep learning in biomedicine
- (2018) Michael Wainberg et al. NATURE BIOTECHNOLOGY
- New machine-learning technologies for computer-aided diagnosis
- (2018) Charles J. Lynch et al. NATURE MEDICINE
- Predicting treatment benefit in multiple myeloma through simulation of alternative treatment effects
- (2018) Joske Ubels et al. Nature Communications
- Artificial intelligence-enabled healthcare delivery
- (2018) Sandeep Reddy et al. JOURNAL OF THE ROYAL SOCIETY OF MEDICINE
- A primer on deep learning in genomics
- (2018) James Zou et al. NATURE GENETICS
- The practical implementation of artificial intelligence technologies in medicine
- (2018) Jianxing He et al. NATURE MEDICINE
- High-performance medicine: the convergence of human and artificial intelligence
- (2018) Eric J. Topol NATURE MEDICINE
- Artificial intelligence in healthcare
- (2018) Kun-Hsing Yu et al. Nature Biomedical Engineering
- Prospective Evaluation of Magnetic Resonance Imaging and [18F]Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography at Diagnosis and Before Maintenance Therapy in Symptomatic Patients With Multiple Myeloma Included in the IFM/DFCI 2009 Trial: Results of the IMAJEM Study
- (2017) Philippe Moreau et al. JOURNAL OF CLINICAL ONCOLOGY
- Role of 18 F-FDG PET/CT in the diagnosis and management of multiple myeloma and other plasma cell disorders: a consensus statement by the International Myeloma Working Group
- (2017) Michele Cavo et al. LANCET ONCOLOGY
- Automated database-guided expert-supervised orientation for immunophenotypic diagnosis and classification of acute leukemia
- (2017) L Lhermitte et al. LEUKEMIA
- Next Generation Flow for highly sensitive and standardized detection of minimal residual disease in multiple myeloma
- (2017) J Flores-Montero et al. LEUKEMIA
- A gene expression signature distinguishes innate response and resistance to proteasome inhibitors in multiple myeloma
- (2017) A K Mitra et al. Blood Cancer Journal
- Artificial intelligence in healthcare: past, present and future
- (2017) Fei Jiang et al. JOURNAL OF INVESTIGATIVE MEDICINE
- Gene expression inference with deep learning
- (2016) Yifei Chen et al. BIOINFORMATICS
- Phenotypic and genomic analysis of multiple myeloma minimal residual disease tumor cells: a new model to understand chemoresistance
- (2016) B. Paiva et al. BLOOD
- Hierarchy for targeting prosurvival BCL2 family proteins in multiple myeloma: pivotal role of MCL1
- (2016) J.-N. Gong et al. BLOOD
- Implementation of erythroid lineage analysis by flow cytometry in diagnostic models for myelodysplastic syndromes
- (2016) Eline M.P. Cremers et al. HAEMATOLOGICA
- First Experience with Chemokine Receptor CXCR4-Targeted PET Imaging of Patients with Solid Cancers
- (2016) T. Vag et al. JOURNAL OF NUCLEAR MEDICINE
- Visualization and analysis of gene expression in tissue sections by spatial transcriptomics
- (2016) P. L. Stahl et al. SCIENCE
- Automated analysis of acute myeloid leukemia minimal residual disease using a support vector machine
- (2016) Wanmao Ni et al. Oncotarget
- Implementation of erythroid lineage analysis by flow cytometry in diagnostic models for myelodysplastic syndromes
- (2016) Eline M.P. Cremers et al. HAEMATOLOGICA
- In vivo molecular imaging of chemokine receptor CXCR4 expression in patients with advanced multiple myeloma
- (2015) K. Philipp-Abbrederis et al. EMBO Molecular Medicine
- Revised International Staging System for Multiple Myeloma: A Report From International Myeloma Working Group
- (2015) Antonio Palumbo et al. JOURNAL OF CLINICAL ONCOLOGY
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Machine learning applications in genetics and genomics
- (2015) Maxwell W. Libbrecht et al. NATURE REVIEWS GENETICS
- Cross-study validation for the assessment of prediction algorithms
- (2014) Christoph Bernau et al. BIOINFORMATICS
- Monoclonal antibodies: potential new therapeutic treatment against multiple myeloma
- (2013) Alessandro Allegra et al. EUROPEAN JOURNAL OF HAEMATOLOGY
- New orally active proteasome inhibitors in multiple myeloma
- (2013) Alessandro Allegra et al. LEUKEMIA RESEARCH
- Critical assessment of automated flow cytometry data analysis techniques
- (2013) Nima Aghaeepour et al. NATURE METHODS
- Increase of novel biomarkers for oxidative stress in patients with plasma cell disorders and in multiple myeloma patients with bone lesions
- (2012) Sebastiano Gangemi et al. INFLAMMATION RESEARCH
- A gene expression signature for high-risk multiple myeloma
- (2012) R Kuiper et al. LEUKEMIA
- Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing
- (2012) Marco Gerlinger et al. NEW ENGLAND JOURNAL OF MEDICINE
- ABT-737 is highly effective against molecular subgroups of multiple myeloma
- (2011) L. Bodet et al. BLOOD
- Laser-Induced Breakdown Spectroscopy (LIBS), Part I: Review of Basic Diagnostics and Plasma—Particle Interactions: Still-Challenging Issues within the Analytical Plasma Community
- (2010) David W. Hahn et al. APPLIED SPECTROSCOPY
- Novel therapeutic strategies in multiple myeloma: role of the heat shock protein inhibitors
- (2010) Alessandro Allegra et al. EUROPEAN JOURNAL OF HAEMATOLOGY
- A high-risk signature for patients with multiple myeloma established from the molecular classification of human myeloma cell lines
- (2010) J. Moreaux et al. HAEMATOLOGICA
- High-risk myeloma: a gene expression based risk-stratification model for newly diagnosed multiple myeloma treated with high-dose therapy is predictive of outcome in relapsed disease treated with single-agent bortezomib or high-dose dexamethasone
- (2008) F. Zhan et al. BLOOD
- Many facets of bortezomib resistance/susceptibility
- (2008) S. Kumar et al. BLOOD
- Flow cytometric immunophenotyping for hematologic neoplasms
- (2008) F. E. Craig et al. BLOOD
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