1
Impact of White Matter Hyperintensities on Nonverbal Cognition Through Structural Disconnections in Poststroke Aphasia
2
Statistical and machine learning methods for spatially resolved transcriptomics data analysis
3
Advances in Machine Learning Approaches to Heart Failure with Preserved Ejection Fraction.
4
Proactive vs Reactive Machine Learning in Health Care: Lessons From the COVID-19 Pandemic.
5
A Review of Fusion Methods for Omics and Imaging Data
6
Evaluating the state of the art in missing data imputation for clinical data
7
Deep Radiotranscriptomics of Non-Small Cell Lung Carcinoma for Assessing Molecular and Histology Subtypes with a Data-Driven Analysis
8
Early Prediction of Mortality in Critical Care Setting in Sepsis Patients Using Structured Features and Unstructured Clinical Notes
9
Deep-Learning Radiomics for Discrimination Conversion of Alzheimer's Disease in Patients With Mild Cognitive Impairment: A Study Based on 18F-FDG PET Imaging
10
Improved Accuracy in Predicting the Best Sensor Fusion Architecture for Multiple Domains
11
Diagnosis of Diabetes Mellitus Using Gradient Boosting Machine (LightGBM)
12
The ethics of machine learning-based clinical decision support: an analysis through the lens of professionalisation theory
13
The role of machine learning in clinical research: transforming the future of evidence generation
14
Explainable Dynamic Multimodal Variational Autoencoder for the Prediction of Patients With Suspected Central Precocious Puberty
15
A cognitive IoT-based framework for effective diagnosis of COVID-19 using multimodal data
16
Machine Learning/Artificial Intelligence for Sensor Data Fusion–Opportunities and Challenges
17
Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics
18
Multimodal temporal machine learning for Bipolar Disorder and Depression Recognition
19
Precision Health Care Elements, Definitions, and Strategies for Patients with Diabetes: A Literature Review
20
Interpretability of Machine Learning Solutions in Public Healthcare: The CRISP-ML Approach
21
Computer-aided diagnosis of hepatocellular carcinoma fusing imaging and structured health data
22
Accessory pathway analysis using a multimodal deep learning model
23
Richer fusion network for breast cancer classification based on multimodal data
24
How machine learning is embedded to support clinician decision making: an analysis of FDA-approved medical devices
25
Early identification of epilepsy surgery candidates: A multicenter, machine learning study
26
Detecting Risk Gene and Pathogenic Brain Region in EMCI Using a Novel GERF Algorithm Based on Brain Imaging and Genetic Data
27
Bidirectional Representation Learning From Transformers Using Multimodal Electronic Health Record Data to Predict Depression
28
Multimodal tensor-based method for integrative and continuous patient monitoring during postoperative cardiac care
29
Multimodal temporal-clinical note network for mortality prediction
30
Machine Learning for Localizing Epileptogenic-Zone in the Temporal Lobe: Quantifying the Value of Multimodal Clinical-Semiology and Imaging Concordance
31
Multimodal deep learning models for early detection of Alzheimer’s disease stage
32
Heterogeneity and Classification of Recent Onset Psychosis and Depression: A Multimodal Machine Learning Approach
33
Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond
34
Deep Learning Based Multimodal Progression Modeling for Alzheimer’s Disease
35
Robust hybrid deep learning models for Alzheimer's progression detection
36
A multilayer multimodal detection and prediction model based on explainable artificial intelligence for Alzheimer’s disease
37
What Every Reader Should Know About Studies Using Electronic Health Record Data but May Be Afraid to Ask
38
On the Application of Advanced Machine Learning Methods to Analyze Enhanced, Multimodal Data from Persons Infected with COVID-19
39
Method of the Year: spatially resolved transcriptomics
40
Mixture Model Framework for Traumatic Brain Injury Prognosis Using Heterogeneous Clinical and Outcome Data
41
A Predictive Model for Parkinson’s Disease Reveals Candidate Gene Sets for Progression Subtype
42
Machine‐learning radiomics to predict early recurrence in perihilar cholangiocarcinoma after curative resection
43
Multimodal Machine Learning Workflows for Prediction of Psychosis in Patients With Clinical High-Risk Syndromes and Recent-Onset Depression
44
Multimodal fusion with deep neural networks for leveraging CT imaging and electronic health record: a case-study in pulmonary embolism detection
45
Predicting mortality in critically ill patients with diabetes using machine learning and clinical notes
46
Multimodal Spatio-Temporal Deep Learning Approach for Neonatal Postoperative Pain Assessment
47
Training confounder-free deep learning models for medical applications
48
Improving Clinical Outcome Predictions Using Convolution over Medical Entities with Multimodal Learning
49
An Explainable Multimodal Neural Network Architecture for Predicting Epilepsy Comorbidities Based on Administrative Claims Data
50
Accurately Differentiating Between Patients With COVID-19, Patients With Other Viral Infections, and Healthy Individuals: Multimodal Late Fusion Learning Approach
51
Prediction of breast cancer distant recurrence using natural language processing and knowledge-guided convolutional neural network
52
Multimodal multitask deep learning model for Alzheimer's disease progression detection based on time series data
53
Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines
54
A novel CERNNE approach for predicting Parkinson's Disease-associated genes and brain regions based on multimodal imaging genetics data
55
Prediction of Type II Diabetes Onset with Computed Tomography and Electronic Medical Records
56
Robust normalization and transformation techniques for constructing gene coexpression networks from RNA-seq data
57
A Comparison of Pre-trained Vision-and-Language Models for Multimodal Representation Learning across Medical Images and Reports
58
Precision Health Data: Requirements, Challenges and Existing Techniques for Data Security and Privacy
59
Accurately Differentiating COVID-19, Other Viral Infection, and Healthy Individuals Using Multimodal Features via Late Fusion Learning
60
Combining structured and unstructured data for predictive models: a deep learning approach
61
A machine-learning framework for robust and reliable prediction of short- and long-term treatment response in initially antipsychotic-naïve schizophrenia patients based on multimodal neuropsychiatric data
62
A multidimensional precision medicine approach identifies an autism subtype characterized by dyslipidemia
63
Improving protein-protein interactions prediction accuracy using XGBoost feature selection and stacked ensemble classifier
64
SwiftIDS: Real-time intrusion detection system based on LightGBM and parallel intrusion detection mechanism
65
Artificial intelligence-enabled fully automated detection of cardiac amyloidosis using electrocardiograms and echocardiograms
66
Solutions for Unexpected Challenges Encountered when Integrating Research Genomics Results into the EHR
67
Auxiliary diagnosis of heterogeneous data of Parkinson’s disease based on improved convolution neural network
68
An Efficient Combination among sMRI, CSF, Cognitive Score, and APOE ε4 Biomarkers for Classification of AD and MCI Using Extreme Learning Machine
69
Radiogenomics model for overall survival prediction of glioblastoma
70
Wearable Monitoring and Interpretable Machine Learning Can Objectively Track Progression in Patients during Cardiac Rehabilitation
71
Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation study
72
Clinical and Public Health Implications of 2019 Endocrine Society Guidelines for Diagnosis of Diabetes in Older Adults
73
SARS-COV-2 comorbidity network and outcome in hospitalized patients in Crema, Italy
74
Multimodal mental health analysis in social media
75
Machine learning classification of ADHD and HC by multimodal serotonergic data
76
Predicting Alzheimer’s Disease Conversion From Mild Cognitive Impairment Using an Extreme Learning Machine-Based Grading Method With Multimodal Data
77
Deep learning radiomics can predict axillary lymph node status in early-stage breast cancer
78
Multi‐dimensional predictions of psychotic symptoms via machine learning
79
Radiogenomics predicts the expression of microRNA-1246 in the serum of esophageal cancer patients
80
Multimodal Data Analysis of Alzheimer's Disease Based on Clustering Evolutionary Random Forest
81
Multimodal Fusion of Imaging and Genomics for Lung Cancer Recurrence Prediction
82
A distributed multitask multimodal approach for the prediction of Alzheimer’s disease in a longitudinal study
83
Elaboration of a multimodal MRI-based radiomics signature for the preoperative prediction of the histological subtype in patients with non-small-cell lung cancer
84
An unsupervised learning approach to identify novel signatures of health and disease from multimodal data
85
U1 snRNP regulates cancer cell migration and invasion in vitro
86
Predicting breast cancer risk using personal health data and machine learning models
87
Med2Meta: Learning Representations of Medical Concepts with Meta-Embeddings
88
Bimodal learning via trilogy of skip-connection deep networks for diabetic retinopathy risk progression identification
89
Predicting rehospitalization within 2 years of initial patient admission for a major depressive episode: a multimodal machine learning approach
90
Making work visible for electronic phenotype implementation: Lessons learned from the eMERGE network
91
Key challenges for delivering clinical impact with artificial intelligence
92
Dissecting racial bias in an algorithm used to manage the health of populations
93
Prediction and Classification of Alzheimer’s Disease Based on Combined Features From Apolipoprotein-E Genotype, Cerebrospinal Fluid, MR, and FDG-PET Imaging Biomarkers
94
Mixed Pooling Multi-View Attention Autoencoder for Representation Learning in Healthcare
95
Predicting risk for Alcohol Use Disorder using longitudinal data with multimodal biomarkers and family history: a machine learning study
96
Multitask Representation Learning for Multimodal Estimation of Depression Level
97
Using Machine Learning to Integrate Socio-Behavioral Factors in Predicting Cardiovascular-Related Mortality Risk
98
Early Prediction of Acute Kidney Injury in Critical Care Setting Using Clinical Notes and Structured Multivariate Physiological Measurements
99
Mixture-based Multiple Imputation Model for Clinical Data with a Temporal Dimension
100
MLMDA: a machine learning approach to predict and validate MicroRNA–disease associations by integrating of heterogenous information sources
101
A radiogenomics signature for predicting the clinical outcome of bladder urothelial carcinoma
102
Integration of Multimodal Data for Breast Cancer Classification Using a Hybrid Deep Learning Method
103
Predicting MCI Status From Multimodal Language Data Using Cascaded Classifiers
104
Residual convolutional neural network for predicting response of transarterial chemoembolization in hepatocellular carcinoma from CT imaging
105
Exploring characteristic features of attention-deficit/hyperactivity disorder: findings from multi-modal MRI and candidate genetic data
106
Development of a targeted client communication intervention to women using an electronic maternal and child health registry: a qualitative study
107
Multimodal Assessment of Parkinson's Disease: A Deep Learning Approach
108
Toward differential diagnosis of autism spectrum disorder using multimodal behavior descriptors and executive functions
109
A Multimodal Deep Neural Network for Human Breast Cancer Prognosis Prediction by Integrating Multi-Dimensional Data
110
A Longitudinal Big Data Approach for Precision Health
111
Machine-learning Prognostic Models from the 2014–16 Ebola Outbreak: Data-harmonization Challenges, Validation Strategies, and mHealth Applications
112
Multimodal Machine Learning-based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data
113
Identifying sub-phenotypes of acute kidney injury using structured and unstructured electronic health record data with memory networks
114
Identification of Predictive Sub-Phenotypes of Acute Kidney Injury using Structured and Unstructured Electronic Health Record Data with Memory Networks
115
Identifying Breast Cancer Distant Recurrences from Electronic Health Records Using Machine Learning
116
Modeling longitudinal imaging biomarkers with parametric Bayesian multi‐task learning
117
Radiological images and machine learning: trends, perspectives, and prospects
118
Recurrent convolutional neural network based multimodal disease risk prediction
119
American Geriatrics Society 2019 Updated AGS Beers Criteria® for Potentially Inappropriate Medication Use in Older Adults
120
Machine learning reveals multimodal MRI patterns predictive of isocitrate dehydrogenase and 1p/19q status in diffuse low- and high-grade gliomas
121
Recent Advances in Supervised Dimension Reduction: A Survey
122
Combining multimodal imaging and treatment features improves machine learning‐based prognostic assessment in patients with glioblastoma multiforme
123
Combining heterogeneous data sources for neuroimaging based diagnosis: re-weighting and selecting what is important
124
Machine-learning-based patient-specific prediction models for knee osteoarthritis
125
Predicting adverse drug reactions of combined medication from heterogeneous pharmacologic databases
126
Deep learning for healthcare: review, opportunities and challenges
127
Characterizing Design Patterns of EHR-Driven Phenotype Extraction Algorithms
128
A Deep Automated Skeletal Bone Age Assessment Model with Heterogeneous Features Learning
129
Effective feature learning and fusion of multimodality data using stage‐wise deep neural network for dementia diagnosis
130
Prediction Models of Functional Outcomes for Individuals in the Clinical High-Risk State for Psychosis or With Recent-Onset Depression: A Multimodal, Multisite Machine Learning Analysis
131
Big Data and Data Science in Critical Care.
132
A kernel machine method for detecting higher order interactions in multimodal datasets: Application to schizophrenia
133
Multimodal Machine Learning for Automated ICD Coding
134
Using clinical Natural Language Processing for health outcomes research: Overview and actionable suggestions for future advances
135
Machine learning–based prediction of clinical pain using multimodal neuroimaging and autonomic metrics
136
PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation
137
MRI predictors of amyloid pathology: results from the EMIF-AD Multimodal Biomarker Discovery study
138
Multimodal skin lesion classification using deep learning
139
Identification of Alzheimer's disease and mild cognitive impairment using multimodal sparse hierarchical extreme learning machine
140
Robust Ensemble Classification Methodology for I123-Ioflupane SPECT Images and Multiple Heterogeneous Biomarkers in the Diagnosis of Parkinson's Disease
141
Development and validation of a novel automated Gleason grade and molecular profile that define a highly predictive prostate cancer progression algorithm-based test
142
RAIM: Recurrent Attentive and Intensive Model of Multimodal Patient Monitoring Data
143
Predicting acute kidney injury in cancer patients using heterogeneous and irregular data
144
A machine learning model to predict the risk of 30-day readmissions in patients with heart failure: a retrospective analysis of electronic medical records data
145
Natural Language Processing for EHR-Based Computational Phenotyping
146
Clinical text classification with rule-based features and knowledge-guided convolutional neural networks
147
Integrating hypertension phenotype and genotype with hybrid non‐negative matrix factorization
148
BRITS: Bidirectional Recurrent Imputation for Time Series
149
Personal Omics for Precision Health
150
Toward achieving precision health
151
Results of the 2016 International Skin Imaging Collaboration International Symposium on Biomedical Imaging challenge: Comparison of the accuracy of computer algorithms to dermatologists for the diagnosis of melanoma from dermoscopic images
152
TieNet: Text-Image Embedding Network for Common Thorax Disease Classification and Reporting in Chest X-Rays
153
Radiogenomic analysis of hypoxia pathway is predictive of overall survival in Glioblastoma
154
LightGBM: A Highly Efficient Gradient Boosting Decision Tree
155
3D-MICE: integration of cross-sectional and longitudinal imputation for multi-analyte longitudinal clinical data
156
Assessment of liver fibrosis in chronic hepatitis B via multimodal data
157
TandemNet: Distilling Knowledge from Medical Images Using Diagnostic Reports as Optional Semantic References
158
Bridging semantics and syntax with graph algorithms-state-of-the-art of extracting biomedical relations.
159
Natural Language Processing for EHR-Based Pharmacovigilance: A Structured Review
160
Distinct multivariate brain morphological patterns and their added predictive value with cognitive and polygenic risk scores in mental disorders
161
Defining a multimodal signature of remote sports concussions
162
Introducing "Genomics and Precision Health".
163
Disease Prediction by Machine Learning Over Big Data From Healthcare Communities
164
Separating generalized anxiety disorder from major depression using clinical, hormonal, and structural MRI data: A multimodal machine learning study
165
Tensor Factorization for Precision Medicine in Heart Failure with Preserved Ejection Fraction
166
Machine Learning of Three-dimensional Right Ventricular Motion Enables Outcome Prediction in Pulmonary Hypertension: A Cardiac MR Imaging Study
167
Predicting Complications in Critical Care Using Heterogeneous Clinical Data
168
Predictive Big Data Analytics: A Study of Parkinson’s Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations
169
High-Accuracy Detection of Early Parkinson's Disease through Multimodal Features and Machine Learning
170
Using Machine Learning to Predict Laboratory Test Results.
171
Tensor factorization toward precision medicine
172
The FAIR Guiding Principles for scientific data management and stewardship
173
The utility of including pathology reports in improving the computational identification of patients
174
Methodological Issues in Predicting Pediatric Epilepsy Surgery Candidates Through Natural Language Processing and Machine Learning
175
Learning probabilistic phenotypes from heterogeneous EHR data
176
Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects
177
Risk prediction for chronic kidney disease progression using heterogeneous electronic health record data and time series analysis
178
Multimodal manifold-regularized transfer learning for MCI conversion prediction
179
Combining macula clinical signs and patient characteristics for age-related macular degeneration diagnosis: a machine learning approach
180
Non-negative matrix factorization of multimodal MRI, fMRI and phenotypic data reveals differential changes in default mode subnetworks in ADHD
181
Data mining for potential adverse drug–drug interactions
182
Alzheimer's Disease Risk Assessment Using Large-Scale Machine Learning Methods
183
A Review of Data Fusion Techniques
184
Multiple Kernel Learning in the Primal for Multimodal Alzheimer’s Disease Classification
185
The Cancer Genome Atlas Pan-Cancer analysis project
186
SemEval-2013 Task 9 : Extraction of Drug-Drug Interactions from Biomedical Texts (DDIExtraction 2013)
187
Ensemble-based regression analysis of multimodal medical data for osteopenia diagnosis
188
Multi-source feature learning for joint analysis of incomplete multiple heterogeneous neuroimaging data
189
Identifying disease sensitive and quantitative trait-relevant biomarkers from multidimensional heterogeneous imaging genetics data via sparse multimodal multitask learning
190
Enhancing Image Analytic Tools by Fusing Quantitative Physiological Values with Image Features
191
Open Source Software in Industry
192
Why Develop Open Source Software? The Role of Non-Pecuniary Benefits, Monetary Rewards and Open Source Licence Type
193
Revisions to the JDL data fusion model
194
Sensor Models and Multisensor Integration
195
Machine Learning Applications in Diagnosis, Treatment and Prognosis of Lung Cancer
196
Detecting Obfuscated Function Clones in Binaries using Machine Learning
197
An intelligent multimodal medical diagnosis system based on patients’ medical questions and structured symptoms for telemedicine
198
OUP accepted manuscript
199
Multimodal machine learning using visual fi elds and peripapillary circular OCT scans in detection of glaucomatous optic neuropathy
200
Multimodal Fusion Strategies for Outcome Prediction in Stroke
201
A novel cryptocurrency price trend forecasting model based on LightGBM
202
ScanMap: Supervised Confounding Aware Non-negative Matrix Factorization for Polygenic Risk Modeling
203
Considerations for Improving the Portability of Electronic Health Record-Based Phenotype Algorithms
204
Bridging semantics and syntax with graph algorithms - state-of-the-art of extracting biomedical relations
205
PHARMACOVIGILANCE FROM ELECTRONIC MEDICAL RECORDS TO REPORT ADVERSE EVENTS
206
Fusing Heterogeneous Data for Alzheimer's Disease Classification
207
Alzheimer’s disease neuroimaging initiative (ADNI): Clinical characterization
208
Ensemble based systems in decision making
209
Medical Applications of NDT Data Fusion
210
Arti fi cial intelligence and machine learning in clinical development: a translational perspective
