A5058659323- Radiomics and Machine Learning in Medical Imaging
- Advanced X-ray and CT Imaging
- Radiation Dose and Imaging
- COVID-19 diagnosis using AI
- Lung Cancer Diagnosis and Treatment
- Radiology practices and education
- Ultrasound in Clinical Applications
- Cardiac Imaging and Diagnostics
- Venous Thromboembolism Diagnosis and Management
- Bone health and osteoporosis research
- Pulmonary Hypertension Research and Treatments
- Medical Imaging Techniques and Applications
- Atomic and Subatomic Physics Research
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Medical Imaging and Analysis
- Bone and Joint Diseases
- Liver Disease Diagnosis and Treatment
- Diet, Metabolism, and Disease
- Diversity and Career in Medicine
- Kidney Stones and Urolithiasis Treatments
- Chemotherapy-induced organ toxicity mitigation
- Artificial Intelligence in Healthcare and Education
- Pediatric Hepatobiliary Diseases and Treatments
- Pancreatic and Hepatic Oncology Research
- Pregnancy and Medication Impact
Yale University
2024-2025
Kuopio University Hospital
2024
Massachusetts General Hospital
2020-2024
University of Eastern Finland
2024
Imaging Center
2024
Babol University of Medical Sciences
2024
Harvard University
2020-2023
Elmhurst Hospital Center
2022-2023
Icahn School of Medicine at Mount Sinai
2022-2023
Mass General Brigham
2023
<h3>Importance</h3> The efficient and accurate interpretation of radiologic images is paramount. <h3>Objective</h3> To evaluate whether a deep learning–based artificial intelligence (AI) engine used concurrently can improve reader performance efficiency in interpreting chest radiograph abnormalities. <h3>Design, Setting, Participants</h3> This multicenter cohort study was conducted from April to November 2021 involved radiologists, including attending thoracic radiology fellows, residents,...
<h3>Importance</h3> Most early lung cancers present as pulmonary nodules on imaging, but these can be easily missed chest radiographs. <h3>Objective</h3> To assess if a novel artificial intelligence (AI) algorithm help detect radiographs at different levels of detection difficulty. <h3>Design, Setting, and Participants</h3> This diagnostic study included 100 posteroanterior radiograph images taken between 2000 2010 adult patients from an ambulatory health care center in Germany image...
Nephrotoxicity and hepatotoxicity are side effects of Cisplatin (CP) therapy.We investigated the role gender in CP-induced nephrotoxicity hepatotoxicity.Low dose CP (1 mg/kg/day; ip) was administered daily to male female Wistar rats for 15 consecutive days. Serum creatinine (Cr), blood urea nitrogen (BUN), malondialdehyde (MDA), nitric oxide (NO) metabolite, magnesium (Mg) levels were determined.The percentage weight loss serum MDA nitrite animals not statistically different. However, BUN,...
To compare prediction of disease outcome, severity, and patient triage in coronavirus 2019 (COVID-19) pneumonia with whole lung radiomics, radiologists' interpretation, clinical variables.This institutional review board-approved retrospective study included 315 adult patients (mean age, 56 years [range, 21-100 years], 190 men, 125 women) COVID-19 who underwent noncontrast chest CT. All (inpatients, n = 210; outpatients, 105) were followed-up for at least 2 weeks to record outcome. Clinical...
Abstract To compare the performance of artificial intelligence (AI) and Radiographic Assessment Lung Edema (RALE) scores from frontal chest radiographs (CXRs) for predicting patient outcomes need mechanical ventilation in COVID-19 pneumonia. Our IRB-approved study included 1367 serial CXRs 405 adult patients (mean age 65 ± 16 years) two sites US (Site A) South Korea B). We recorded information pertaining to demographics (age, gender), smoking history, comorbid conditions (such as cancer,...
As of August 30th, there were in total 25.1 million confirmed cases and 845 thousand deaths caused by coronavirus disease 2019 (COVID-19) worldwide. With overwhelming demands on medical resources, patient stratification based their risks is essential. In this multi-center study, we built prognosis models to predict severity outcomes, combining patients' electronic health records (EHR), which included vital signs laboratory data, with deep learning- CT-based prediction.
Early and accurate diagnosis of Coronavirus disease (COVID-19) is essential for patient isolation contact tracing so that the spread infection can be limited. Computed tomography (CT) provide important information in COVID-19, especially patients with moderate to severe as well those worsening cardiopulmonary status. As an automatic tool, deep learning methods utilized perform semantic segmentation affected lung regions, which establish severity prognosis prediction. Both extent type...
Osteoporosis is the most common metabolic bone disease that not recognized in many elderly people. To determine cause of low back pain, lumbosacral MRI done for a large population who may have gone under dual energy X-ray absorptiometry (DXA). The aim this study was to predict density using lumbar spine signals high risk patients osteoporosis including post-menopausal females and calculate threshold new quantitative MRI-based score be used estimation mass density.82 menopaused females, had...
Background: Fatty liver disease is a common hepatic disorder that remains undiagnosed due to the high number of asymptomatic patients and lack proper noninvasive diagnostic tool. Liver biopsy, gold standard steatosis diagnosis, an invasive method can be replaced by fibroscan. Fibroscan detect with sensitivity specificity, but it not accessible around world. In this study, we compared ultrasonography (US) as cheap device fibroscan in detecting steatosis. Materials Methods: We enrolled 77...
Purpose: We assessed whether a CXR AI algorithm was able to detect missed or mislabeled chest radiograph (CXR) findings in radiology reports. Methods: queried multi-institutional reports search database of 13 million identify all with addendums from 1999-2021. Of the 3469 an addendum, thoracic radiologist excluded where addenda were created for typographic errors, wrong report template, missing sections, uninterpreted signoffs. The remaining contained (279 patients) errors related...
This study was conducted to detect the association between radiologic features of CT pulmonary angiography (CTPA) and embolism severity index (PESI).A total 150 patients with a definite diagnosis PE entered study. The CTPA feature including obstruction index, trunk size, presence backwash contrast, septal morphology, right ventricular (RV) left (LV) dimensions, RV/LV ratio were examined. estimated using PESI. indices PESI measured. Statistical analysis SPSS software. P value < 0.05...
Bone mineral density (BMD), as a gold standard determinant of osteoporosis, assesses only one many characteristics contributing to the bone. Trabecular bone score (TBS) is applied evaluate microarchitecture trabecular A high body mass index (BMI) has been reported have positive correlation with BMD. However, relation between BMI and TBS remained unclear. Therefore, aim this study shed light on associations BMI, T-score, in postmenopausal women without diagnosed underlying disease.In...