Michael A. Jacobs
YOU?
Author Swipe
View article: Direct parieto-occipital connectivity of the amygdala via the parahippocampal segment of the cingulum bundle
Direct parieto-occipital connectivity of the amygdala via the parahippocampal segment of the cingulum bundle Open
Background The amygdala is a key structure involved in memory, emotional processing, and sensory integration. While the cortical connectivity of the amygdala with the frontal and temporal lobes has been extensively studied, its direct conn…
View article: Neighborhood socioeconomic disadvantage is not associated with adverse outcomes following elective spine surgery in older Veterans
Neighborhood socioeconomic disadvantage is not associated with adverse outcomes following elective spine surgery in older Veterans Open
View article: A Multidimensional Connectomics- and Radiomics-Based Advanced Machine-Learning Framework to Distinguish Radiation Necrosis from True Progression in Brain Metastases
A Multidimensional Connectomics- and Radiomics-Based Advanced Machine-Learning Framework to Distinguish Radiation Necrosis from True Progression in Brain Metastases Open
We introduce tumor connectomics, a novel MRI-based complex graph theory framework that describes the intricate network of relationships within the tumor and surrounding tissue, and combine this with multiparametric radiomics (mpRad) in a m…
View article: Exploring Model Architectures for Real-Time Lung Sound Event Detection
Exploring Model Architectures for Real-Time Lung Sound Event Detection Open
View article: Understanding the Impact of Socioeconomic Deprivation on Inpatient Surgical Care Delivery Costs in the Veterans Health Administration
Understanding the Impact of Socioeconomic Deprivation on Inpatient Surgical Care Delivery Costs in the Veterans Health Administration Open
View article: Detection of diffusely abnormal white matter in multiple sclerosis on multiparametric brain MRI using semi-supervised deep learning
Detection of diffusely abnormal white matter in multiple sclerosis on multiparametric brain MRI using semi-supervised deep learning Open
In addition to focal lesions, diffusely abnormal white matter (DAWM) is seen on brain MRI of multiple sclerosis (MS) patients and may represent early or distinct disease processes. The role of MRI-observed DAWM is understudied due to a lac…
View article: AI driven analysis of MRI to measure health and disease progression in FSHD
AI driven analysis of MRI to measure health and disease progression in FSHD Open
View article: The Use of Apparent Diffusion Coefficient Values for Differentiating Bevacizumab-Related Cytotoxicity from Tumor Recurrence and Radiation Necrosis in Glioblastoma
The Use of Apparent Diffusion Coefficient Values for Differentiating Bevacizumab-Related Cytotoxicity from Tumor Recurrence and Radiation Necrosis in Glioblastoma Open
Objectives: Glioblastomas (GBM) are the most common primary invasive neoplasms of the brain. Distinguishing between lesion recurrence and different types of treatment related changes in patients with GBM remains challenging using conventio…
View article: Automatic Active Lesion Tracking in Multiple Sclerosis Using Unsupervised Machine Learning
Automatic Active Lesion Tracking in Multiple Sclerosis Using Unsupervised Machine Learning Open
Background: Identifying active lesions in magnetic resonance imaging (MRI) is crucial for the diagnosis and treatment planning of multiple sclerosis (MS). Active lesions on MRI are identified following the administration of Gadolinium-base…
View article: Who is afraid of Hermy and Jimmy? Relating to and normalizing psychosis through theater.
Who is afraid of Hermy and Jimmy? Relating to and normalizing psychosis through theater. Open
Theater can promote social change, making space for a wider range of perspectives in society. Engaging individuals with lived experiences of psychosis in theatrical productions could lead to new insights about and acceptance of psychotic e…
View article: Automated Lung Ultrasound Pulmonary Disease Quantification Using an Unsupervised Machine Learning Technique for COVID-19
Automated Lung Ultrasound Pulmonary Disease Quantification Using an Unsupervised Machine Learning Technique for COVID-19 Open
COVID-19 is an ongoing global health pandemic. Although COVID-19 can be diagnosed with various tests such as PCR, these tests do not establish pulmonary disease burden. Whereas point-of-care lung ultrasound (POCUS) can directly assess the …
View article: A Multidimensional Connectomics- and Radiomics-Based Advanced Machine-Learning Framework to Distinguish Radiation Necrosis from True Progression in Brain Metastases
A Multidimensional Connectomics- and Radiomics-Based Advanced Machine-Learning Framework to Distinguish Radiation Necrosis from True Progression in Brain Metastases Open
We introduce tumor connectomics, a novel MRI-based complex graph theory framework that describes the intricate network of relationships within the tumor and surrounding tissue, and combine this with multiparametric radiomics (mpRad) in a m…
View article: Review: When worlds collide – poultry modeling in the ‘Big Data’ era
Review: When worlds collide – poultry modeling in the ‘Big Data’ era Open
Within poultry production systems, models have provided vital decision support, opportunity analysis, and performance optimization capabilities to nutritionists and producers for decades. In recent years, due to the advancement of digital …
View article: Data Partitioning and Statistical Considerations for Association of Radiomic Features to Biological Underpinnings: What Is Needed
Data Partitioning and Statistical Considerations for Association of Radiomic Features to Biological Underpinnings: What Is Needed Open
View article: Lung Cancer Recurrence Risk Prediction through Integrated Deep Learning Evaluation
Lung Cancer Recurrence Risk Prediction through Integrated Deep Learning Evaluation Open
Background: Prognostic risk factors for completely resected stage IA non-small-cell lung cancers (NSCLCs) have advanced minimally over recent decades. Although several biomarkers have been found to be associated with cancer recurrence, the…
View article: Radiomic Analysis: Study Design, Statistical Analysis, and Other Bias Mitigation Strategies
Radiomic Analysis: Study Design, Statistical Analysis, and Other Bias Mitigation Strategies Open
Rapid advances in automated methods for extracting large numbers of quantitative features from medical images have led to tremendous growth of publications reporting on radiomic analyses. Translation of these research studies into clinical…
View article: Tumor Connectomics: Mapping the Intra-Tumoral Complex Interaction Network Using Machine Learning
Tumor Connectomics: Mapping the Intra-Tumoral Complex Interaction Network Using Machine Learning Open
The high-level relationships that form complex networks within tumors and between surrounding tissue is challenging and not fully understood. To better understand these tumoral networks, we developed a tumor connectomics framework (TCF) ba…
View article: Long-Term Stability of Gradient Characteristics Warrants Model-Based Correction of Diffusion Weighting Bias
Long-Term Stability of Gradient Characteristics Warrants Model-Based Correction of Diffusion Weighting Bias Open
The study aims to test the long-term stability of gradient characteristics for model-based correction of diffusion weighting (DW) bias in an apparent diffusion coefficient (ADC) for multisite imaging trials. Single spin echo (SSE) DWI of a…
View article: Cross-Domain Federated Learning in Medical Imaging
Cross-Domain Federated Learning in Medical Imaging Open
Federated learning is increasingly being explored in the field of medical imaging to train deep learning models on large scale datasets distributed across different data centers while preserving privacy by avoiding the need to transfer sen…
View article: Multi‐Site Concordance of Diffusion‐Weighted Imaging Quantification for Assessing Prostate Cancer Aggressiveness
Multi‐Site Concordance of Diffusion‐Weighted Imaging Quantification for Assessing Prostate Cancer Aggressiveness Open
Background Diffusion‐weighted imaging (DWI) is commonly used to detect prostate cancer, and a major clinical challenge is differentiating aggressive from indolent disease. Purpose To compare 14 site‐specific parametric fitting implementati…
View article: Diagnosis of Medical Images Using Cloud-Deep Learning System
Diagnosis of Medical Images Using Cloud-Deep Learning System Open
Diagnosis of brain tumors is one of the most severe medical problems that affect thousands of people each year in the United States. Manual classification of cancerous tumors through examination of MRI images is a difficult task even for t…
View article: Multiparametric magnetic resonance imaging to characterize cabotegravir long‐acting formulation depot kinetics in healthy adult volunteers
Multiparametric magnetic resonance imaging to characterize cabotegravir long‐acting formulation depot kinetics in healthy adult volunteers Open
Aim Cabotegravir long‐acting (LA) intramuscular (IM) injection is being investigated for HIV preexposure prophylaxis due to its potent antiretroviral activity and infrequent dosing requirement. A subset of healthy adult volunteers particip…
View article: Multiparametric radiomic tissue signature and machine learning for distinguishing radiation necrosis from tumor progression after stereotactic radiosurgery
Multiparametric radiomic tissue signature and machine learning for distinguishing radiation necrosis from tumor progression after stereotactic radiosurgery Open
Background Stereotactic radiosurgery (SRS) may cause radiation necrosis (RN) that is difficult to distinguish from tumor progression (TP) by conventional MRI. We hypothesize that MRI-based multiparametric radiomics (mpRad) and machine lear…
View article: A Deep Learning System for Synthetic Knee Magnetic Resonance Imaging
A Deep Learning System for Synthetic Knee Magnetic Resonance Imaging Open
Objectives The aim of this study was to determine the feasibility and performance of a deep learning system used to create synthetic artificial intelligence‐based fat-suppressed magnetic resonance imaging (AFSMRI) scans of the knee. Materi…
View article: RADT-14. COMPARISON OF MACHINE LEARNING ALGORITHMS IN DISTINGUISHING RADIATION NECROSIS FROM PROGRESSION OF BRAIN METASTASES TREATED WITH STEREOTACTIC RADIOSURGERY (SRS)
RADT-14. COMPARISON OF MACHINE LEARNING ALGORITHMS IN DISTINGUISHING RADIATION NECROSIS FROM PROGRESSION OF BRAIN METASTASES TREATED WITH STEREOTACTIC RADIOSURGERY (SRS) Open
PURPOSE To test the effectiveness of machine learning algorithms in distinguishing radiation necrosis (RN) from tumor progression (TP) using MRI radiomic features. METHODS Brain metastases were treated with SRS to a median dose of 18Gy. Le…
View article: External Validation Of A Radiomics-Based Machine Learning Model For Distinguishing Radiation Necrosis From Progression Of Brain Metastases Treated With Stereotactic Radiosurgery
External Validation Of A Radiomics-Based Machine Learning Model For Distinguishing Radiation Necrosis From Progression Of Brain Metastases Treated With Stereotactic Radiosurgery Open
View article: Brain metabolites in cholinergic and glutamatergic pathways are altered by pancreatic cancer cachexia
Brain metabolites in cholinergic and glutamatergic pathways are altered by pancreatic cancer cachexia Open
Background Cachexia is a major cause of morbidity in pancreatic ductal adenocarcinoma (PDAC) patients. Our purpose was to understand the impact of PDAC‐induced cachexia on brain metabolism in PDAC xenograft studies, to gain new insights in…
View article: Integrated Multiparametric Radiomics and Informatics System for Characterizing Breast Tumor Characteristics with the OncotypeDX Gene Assay
Integrated Multiparametric Radiomics and Informatics System for Characterizing Breast Tumor Characteristics with the OncotypeDX Gene Assay Open
Optimal use of multiparametric magnetic resonance imaging (mpMRI) can identify key MRI parameters and provide unique tissue signatures defining phenotypes of breast cancer. We have developed and implemented a new machine-learning informati…
View article: 59. A RADIOMICS-BASED MACHINE LEARNING MODEL FOR DISTINGUISHING RADIATION NECROSIS FROM PROGRESSION OF BRAIN METASTASES TREATED WITH STEREOTACTIC RADIOSURGERY (SRS)
59. A RADIOMICS-BASED MACHINE LEARNING MODEL FOR DISTINGUISHING RADIATION NECROSIS FROM PROGRESSION OF BRAIN METASTASES TREATED WITH STEREOTACTIC RADIOSURGERY (SRS) Open
PURPOSE This study aims to test whether MRI radiomic signatures can distinguish radiation necrosis (RN) from tumor progression (TP) in a multi-institution dataset using machine learning. METHODS Brain metastases treated with SRS were follo…
View article: Longitudinal functional and imaging outcome measures in FKRP limb-girdle muscular dystrophy
Longitudinal functional and imaging outcome measures in FKRP limb-girdle muscular dystrophy Open