Martin M. Miner

Martin M. Miner

Warren Alpert School Of Medicine, Brown University, Providence, Ricorrespondencemartin_miner@brown.edu

Direct Impact

Concepts for which Martin M Miner has direct influence:

erectile dysfunction
testosterone replacement therapy
testim registry
sexual function
artificial intelligence
12 months
benign prostatic hyperplasia

External impact

Concepts related to the work of other authors for which Martin M Miner has influence:

erectile dysfunction
chronic kidney
prostate cancer
metabolic syndrome
coronary artery
machine learning
serum biomarkers

Prominent publications by Martin M. Miner

KOL-Index: 175 Chronic kidney disease (CKD) and cardiovascular disease (CVD) together result in an enormous burden on global healthcare. The estimated glomerular filtration rate (eGFR) is a well-established biomarker of CKD and is associated with adverse cardiac events. This review highlights the link between eGFR reduction and that of atherosclerosis progression, which increases the risk of adverse ...
Known for
Ckd Cardiovascular | Phenotypes Models | Enormous | Accurate Automated Cvd Assessments
KOL-Index: 127 Cardiovascular disease (CVD) is one of the leading causes of morbidity and mortality in the United States of America and globally. Carotid arterial plaque, a cause and also a marker of such CVD, can be detected by various non-invasive imaging modalities such as magnetic resonance imaging (MRI), computer tomography (CT), and ultrasound (US). Characterization and classification of carotid ...
Known for
Classification Carotid | Varying Hausdorff Values | Transfer Learning | Non-Invasive Imaging Modalities
KOL-Index: 122 Purpose of ReviewWe review the recent literature on the hypothesized temporal relationship between subclinical cardiovascular disease (CVD), vascular erectile dysfunction (ED), and clinical CVD. In addition, we combine emerging research with expert consensus guidelines such as The Princeton Consensus III to provide a preventive cardiologist’s perspective toward an ideal approach to ...
Known for
Intermediate Intermediate | Coronary Artery Calcium | Preventive Cardiologist’s | Cvd Vascular
KOL-Index: 96 Artificial intelligence (AI) has penetrated the field of medicine, particularly the field of radiology. Since its emergence, the highly virulent coronavirus disease 2019 (COVID-19) has infected over 10 million people, leading to over 500,000 deaths as of July 1st, 2020. Since the outbreak began, almost 28,000 articles about COVID-19 have been published (https://pubmed.ncbi.nlm.nih.gov); ...
Known for
Lung Injury | Artificial | Highly Virulent Coronavirus | Probabilities
KOL-Index: 90 We evaluated the association between automatically measured carotid total plaque area (TPA) and the estimated glomerular filtration rate (eGFR), a biomarker of chronic kidney disease (CKD). Automated average carotid intima-media thickness (cIMTave) and TPA measurements in carotid ultrasound (CUS) were performed using AtheroEdge (AtheroPoint). Pearson correlation coefficient (CC) was then ...
Known for
Automated Tpa | Left Cca | Atheropoint | Morphological Carotid
KOL-Index: 89 The objectives of this study are to (1) examine the "10-year cardiovascular risk" in the common carotid artery (CCA) versus carotid bulb using an integrated calculator called "AtheroEdge Composite Risk Score 2.0" (AECRS2.0) and (2) evaluate the performance of AECRS2.0 against "conventional cardiovascular risk calculators." These objectives are met by measuring (1) image-based phenotypes and ...
Known for
Conventional Cardiovascular | 55 ± | 67 Males | 1 ∼13
KOL-Index: 84 Background: For COVID-19 lung severity, segmentation of lungs on computed tomography (CT) is the first crucial step. Current deep learning (DL)-based Artificial Intelligence (AI) models have a bias in the training stage of segmentation because only one set of ground truth (GT) annotations are evaluated. We propose a robust and stable inter-variability analysis of CT lung segmentation in ...
Known for
Tracers Computing | Annotations | Models Psp | Tomography Covid-19
KOL-Index: 78 Cardiovascular diseases (CVDs) are the top ten leading causes of death worldwide. Atherosclerosis disease in the arteries is the main cause of the CVD, leading to myocardial infarction and stroke. The two primary image-based phenotypes used for monitoring the atherosclerosis burden is carotid intima-media thickness (cIMT) and plaque area (PA). Earlier segmentation and measurement methods ...
Known for
Modern Automated Methods | Fast-Changing Technology | Lumen-Intima Media-Adventitia Interface | Primary Image-Based Phenotypes
KOL-Index: 69 RECENT FINDINGS: Cardiovascular disease (CVD) is the leading cause of mortality and poses challenges for healthcare providers globally. Risk-based approaches for the management of CVD are becoming popular for recommending treatment plans for asymptomatic individuals. Several conventional predictive CVD risk models based do not provide an accurate CVD risk assessment for patients with ...
Known for
Models Noninvasive | Powerful Ai-Based Strategies | Artificial Intelligence Algorithms | Input Nonlinear Variations
KOL-Index: 65 Background: Vascular age (VA) has recently emerged for CVD risk assessment and can either be computed using conventional risk factors (CRF) or by using carotid intima-media thickness (cIMT) derived from carotid ultrasound (CUS). This study investigates a novel method of integrating both CRF and cIMT for estimating VA [so-called integrated VA (IVA)]. Further, the study analyzes and compares ...
Known for
Multivariate Linear Regression | Lr-Based Model | Carotid Intima-Media Thickness | Crf Cimt

Warren Alpert School of Medicine, Brown University, Providence, RICorrespondencemartin_miner@brown.edu

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