A5046568443- AI in cancer detection
- Radiomics and Machine Learning in Medical Imaging
- Oral and Maxillofacial Pathology
- Salivary Gland Tumors Diagnosis and Treatment
- Dental Research and COVID-19
- Clinical Reasoning and Diagnostic Skills
- Ear and Head Tumors
- Breast Cancer Treatment Studies
- Innovations in Medical Education
- Long-Term Effects of COVID-19
- dental development and anomalies
- COVID-19 Clinical Research Studies
- Renal Transplantation Outcomes and Treatments
- Renal and Vascular Pathologies
- Oral Health Pathology and Treatment
- Myasthenia Gravis and Thymoma
- Organ Donation and Transplantation
- Dermatological and COVID-19 studies
- Educational Strategies and Epistemologies
- Neurofibromatosis and Schwannoma Cases
- Optical Coherence Tomography Applications
- Periodontal Regeneration and Treatments
- Skin and Cellular Biology Research
- Brain Metastases and Treatment
- Genetic and rare skin diseases.
Icahn School of Medicine at Mount Sinai
2020-2025
University of Michigan
2024-2025
Nia Association
2024
American Dental Education Association
2022-2024
University of Washington
2024
John Wiley & Sons (United States)
2022-2024
Mount Sinai Hospital
2016-2021
Mount Sinai Medical Center
2017
BACKGROUND Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) and its associated clinical syndrome COVID-19 are causing overwhelming morbidity mortality around the globe, disproportionately affecting New York City. A comprehensive, integrative autopsy series that advances mechanistic discussion surrounding this disease process is still lacking. METHODS Autopsies were performed at Mount Sinai Hospital on 67 positive patients data from records obtained Data Warehouse. The...
The use of self-supervised learning (SSL) to train pathology foundation models has increased substantially in the past few years. Notably, several trained on large quantities clinical data have been made publicly available recent months. This will significantly enhance scientific research computational and help bridge gap between deployment. With increase availability public different sizes, using algorithms datasets, it becomes important establish a benchmark compare performance such...
Salivary gland tumors represent a diverse group of neoplasms that occasionally pose diagnostic challenge for pathologists, particularly with limited sampling. Gene fusions, which may reflect genetic drivers, are increasingly recognized in subset these neoplasms, and can be leveraged purposes. We performed retrospective analysis on cohort 80 benign malignant salivary tumors, enriched subtypes known to harbor recurrent fusion events, validate the use targeted RNA sequencing assay detect...
Recent breakthroughs in self-supervised learning have enabled the use of large unlabeled datasets to train visual foundation models that can generalize a variety downstream tasks. While this training paradigm is well suited for medical domain where annotations are scarce, large-scale pre-training domain, and particular pathology, has not been extensively studied. Previous work pathology leveraged smaller both evaluating performance. The aim project largest academic model benchmark most...
ABSTRACT Introduction Despite its utility, peer feedback within higher education curricula has not demonstrated a consistent correlation with academic performance. Student self‐reflection may be one factor of influence, as one's metacognitive assessment can alter perception and processing. Yet, formal instruction on reflection remains rare. This single‐subject study assesses the level students' self‐reflective capabilities through adaptation pilot use rubric based Korthagen's ALACT model....
Diagnosis and classification of oral epithelial dysplasia (OED) is critical to identifying prognosticating patients at risk squamous cell carcinoma (SCC). However, conventional 3-tiered 2-tiered grading systems suffer from poor inter-pathologist agreement, SCC may arise all grades OED. This study evaluated pathologist agreement in OED as p53 wildtype, abnormal, HPV-associated based on recent evidence demonstrating the utility p53/p16 immunohistochemistry (IHC) this setting increased abnormal...
The use of self-supervised learning to train pathology foundation models has increased substantially in the past few years. Notably, several trained on large quantities clinical data have been made publicly available recent months. This will significantly enhance scientific research computational and help bridge gap between deployment. With increase availability public different sizes, using algorithms datasets, it becomes important establish a benchmark compare performance such variety...
Breast cancer (BC) grading plays a critical role in patient management despite the considerable inter- and intra-observer variability, highlighting need for decision support tools to improve reproducibility prognostic accuracy use clinical practice. The objective was evaluate ability of digital artificial intelligence (AI) assay (PDxBr) enrich BC risk categorization predicting recurrence.In our population-based longitudinal development validation study, we enrolled 2075 patients from Mount...
Involvement of deep margins represents a significant challenge in the treatment oropharyngeal cancer, and given practical limitations frozen-section analysis, need exists for real-time, nondestructive intraoperative margin analysis. Wide-field optical coherence tomography (WF-OCT) has been evaluated as tool high-resolution adjunct specimen imaging breast surgery, but its clinical application head neck surgery not explored.To evaluate utility WF-OCT visualizing microstructures at excised oral...
Background : PreciseDx Breast is a digital test that predicts early-stage breast cancer recurrence within 6-years of diagnosis. Materials and Methods Using hematoxylin eosin-stained whole slide images invasive (IBC) artificial intelligence-enabled Morphology Feature Array, microanatomic features are generated. Morphometric attributes in combination with patient age, tumor size, stage lymph node status disease free survival using proprietary algorithm. Here, analytical validation the...
Context.— The diagnosis of some infectious diseases requires their identification in tissue specimens. As institutions adopt digital pathology for primary diagnosis, the limits microorganism detection from images must be delineated. Objective.— To assess reliability digitized histochemical and immunohistochemical stains commonly used pathology. Design.— Original glass slides 620 surgical cases evaluated presence microorganisms were digitized. Immunohistochemical included those herpes simplex...
Abstract Purpose/objectives The ability to give and receive feedback is a key skill develop during predoctoral dental education, the use of peer specifically offers distinct benefits including different understanding material due peers’ proximity knowledge development assisting with overburdened instructors. However, it unclear if similar quality instructor feedback. Methods Dental students in two graduation years provided quantitative qualitative on case‐based oral maxillofacial pathology...
INSM1 has rapidly emerged as a robust marker for neuroendocrine (NE) differentiation, prompting the use of standalone NE differentiation in various sites. staining could be an especially practical tool evaluating HPV-associated oropharyngeal squamous cell carcinoma (HPV-OPSCCs) because high-grade transformation may exceedingly difficult to recognize on morphologic grounds alone, even though it portends highly aggressive clinical behavior. The purpose this study was determine incidence...
The purpose of this paper is to explore the benefits pass-fail grading as opposed more frequently used letter grade system in dental education.A can enhance student well-being, facilitate intrinsic motivation and promote competency-based education.Although review primarily based on literature from North America, discussion still relevant European audiences because issue pass fail an inherent all types education.There are two kinds schemes that fall a continuum ranging use only grades being...
Journal of Dental Education is published in 15 issues per year.FTE-based pricing, based on the overall demand and size type subscribing institution (academic, government, hospital or corporate), applies for this Journal.