A5047334337- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
- COVID-19 Clinical Research Studies
- Artificial Intelligence in Healthcare and Education
- Long-Term Effects of COVID-19
- Pancreatitis Pathology and Treatment
- Machine Learning in Healthcare
- Renal cell carcinoma treatment
- Amyotrophic Lateral Sclerosis Research
- COVID-19 and Mental Health
- MRI in cancer diagnosis
- Radiology practices and education
- Parkinson's Disease Mechanisms and Treatments
- Sepsis Diagnosis and Treatment
- Lysosomal Storage Disorders Research
Rhode Island Hospital
2021-2022
Providence College
2021-2022
John Brown University
2021
Brown University
2020-2021
Cornell University
2017
Background Despite its high sensitivity in diagnosing coronavirus disease 2019 (COVID-19) a screening population, the chest CT appearance of COVID-19 pneumonia is thought to be nonspecific. Purpose To assess performance radiologists United States and China differentiating from viral at CT. Materials Methods In this study, 219 patients with positive COVID-19, as determined reverse-transcription polymerase chain reaction (RT-PCR) abnormal findings, were retrospectively identified seven Chinese...
Background Coronavirus disease 2019 (COVID-19) and pneumonia of other diseases share similar CT characteristics, which contributes to the challenges in differentiating them with high accuracy. Purpose To establish evaluate an artificial intelligence (AI) system for COVID-19 at chest assessing radiologist performance without AI assistance. Materials Methods A total 521 patients positive reverse transcription polymerase chain reaction results abnormal findings were retrospectively identified...
Abstract Haploinsufficiency of progranulin (PGRN) due to mutations in the granulin ( GRN ) gene causes frontotemporal lobar degeneration (FTLD), and complete loss PGRN leads a lysosomal storage disorder, neuronal ceroid lipofuscinosis (NCL). Accumulating evidence suggests that is essential for proper function, but precise mechanisms involved are not known. Here, we show facilitates uptake delivery prosaposin (PSAP), precursor saposin peptides glycosphingolipid degradation. We found reduced...
While COVID-19 diagnosis and prognosis artificial intelligence models exist, very few can be implemented for practical use given their high risk of bias. We aimed to develop a model that addresses notable shortcomings prior studies, integrating it into fully automated triage pipeline examines chest radiographs the presence, severity, progression pneumonia. Scans were collected using DICOM Image Analysis Archive, system communicates with hospital's image repository. The authors over 6,500...
To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration critical illness using CT clinical variables. Clinical data were collected from 981 patients multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features extracted chest of patients. The randomly divided into training, validation, test sets 7:1:2 ratio. A ML consisting model...
Abstract To explore the role of chronic liver disease (CLD) in COVID-19. A total 1439 consecutively hospitalized patients with COVID-19 from one large medical center United States March 16, 2020 to April 23, were retrospectively identified. Clinical characteristics and outcomes compared between without CLD. Postmortem examination 8 critically ill was performed. There no significant difference incidence CLD critical non-critical groups (4.1% vs 2.9%, p = 0.259), or related injury (65.7%...
Abstract Aims To determine if neurologic symptoms at admission can predict adverse outcomes in patients with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). Methods Electronic medical records of 1053 consecutively hospitalized laboratory‐confirmed infection SARS‐CoV‐2 from one large center the USA were retrospectively analyzed. Univariable and multivariable Cox regression analyses performed calculation areas under curve (AUC) concordance index (C‐index). Patients stratified...
Abstract Purpose: To explore the role of chronic liver disease (CLD) in COVID-19. Methods: A total 1,439 consecutively hospitalized patients with COVID-19 from one large medical center United States March 16, 2020 to April 23, were retrospectively identified. Clinical characteristics and outcomes compared between without CLD. Postmortem examination 8 critically ill was performed. Results: There no significant difference incidence CLD critical non-critical groups (4.1% vs 2.9%, p=0.259), or...