Gregory M. Goldgof
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View article: Interpretable Multiple Instance Learning for Hematologic Diagnosis from Peripheral Blood Smears
Interpretable Multiple Instance Learning for Hematologic Diagnosis from Peripheral Blood Smears Open
View article: Real-world deployment of a fine-tuned pathology foundation model for lung cancer biomarker detection
Real-world deployment of a fine-tuned pathology foundation model for lung cancer biomarker detection Open
Artificial intelligence models using digital histopathology slides stained with hematoxylin and eosin offer promising, tissue-preserving diagnostic tools for patients with cancer. Despite their advantages, their clinical utility in real-wo…
View article: Single GPU Task Adaptation of Pathology Foundation Models for Whole Slide Image Analysis
Single GPU Task Adaptation of Pathology Foundation Models for Whole Slide Image Analysis Open
Pathology foundation models (PFMs) have emerged as powerful tools for analyzing whole slide images (WSIs). However, adapting these pretrained PFMs for specific clinical tasks presents considerable challenges, primarily due to the availabil…
View article: Dr-LLaVA: Visual Instruction Tuning with Symbolic Clinical Grounding
Dr-LLaVA: Visual Instruction Tuning with Symbolic Clinical Grounding Open
Vision-Language Models (VLM) can support clinicians by analyzing medical images and engaging in natural language interactions to assist in diagnostic and treatment tasks. However, VLMs often exhibit "hallucinogenic" behavior, generating te…
View article: Efficacy of the QuitSure App for Smoking Cessation in Adult Smokers: Cross-Sectional Web Survey
Efficacy of the QuitSure App for Smoking Cessation in Adult Smokers: Cross-Sectional Web Survey Open
Background Cigarette smoking remains one of the leading causes of preventable death worldwide. A worldwide study by the World Health Organization concluded that more than 8 million people die every year from smoking, tobacco consumption, a…
View article: Aligning Synthetic Medical Images with Clinical Knowledge using Human Feedback
Aligning Synthetic Medical Images with Clinical Knowledge using Human Feedback Open
Generative models capable of capturing nuanced clinical features in medical images hold great promise for facilitating clinical data sharing, enhancing rare disease datasets, and efficiently synthesizing annotated medical images at scale. …
View article: Efficacy of the QuitSure App for Smoking Cessation in Adult Smokers: Cross-Sectional Web Survey (Preprint)
Efficacy of the QuitSure App for Smoking Cessation in Adult Smokers: Cross-Sectional Web Survey (Preprint) Open
BACKGROUND Cigarette smoking remains one of the leading causes of preventable death worldwide. A worldwide study by the World Health Organization concluded that more than 8 million people die every year from smoking, tobacco consumption, …
View article: Novel computational methods on electronic health record yields new estimates of transfusion‐associated circulatory overload in populations enriched with high‐risk patients
Novel computational methods on electronic health record yields new estimates of transfusion‐associated circulatory overload in populations enriched with high‐risk patients Open
Background Transfusion‐associated circulatory overload (TACO) is a severe adverse reaction (AR) contributing to the leading cause of mortality associated with transfusions. As strategies to mitigate TACO have been increasingly adopted, an …
View article: DeepHeme: A generalizable, bone marrow classifier with hematopathologist-level performance
DeepHeme: A generalizable, bone marrow classifier with hematopathologist-level performance Open
Morphology-based classification of cells in the bone marrow aspirate (BMA) is a key step in the diagnosis and management of hematologic malignancies. However, it is time-intensive and must be performed by expert hematopathologists and labo…
View article: Adaptive laboratory evolution in S. cerevisiae highlights role of transcription factors in fungal xenobiotic resistance
Adaptive laboratory evolution in S. cerevisiae highlights role of transcription factors in fungal xenobiotic resistance Open
In vitro evolution and whole genome analysis were used to comprehensively identify the genetic determinants of chemical resistance in Saccharomyces cerevisiae . Sequence analysis identified many genes contributing to the resistance phenoty…
View article: Defining the Yeast Resistome through<i>in vitro</i>Evolution and Whole Genome Sequencing
Defining the Yeast Resistome through<i>in vitro</i>Evolution and Whole Genome Sequencing Open
Summary In vitro evolution and whole genome analysis were used to comprehensively identify the genetic determinants of chemical resistance in the model microbe, Saccharomyces cerevisiae . Analysis of 355 curated, laboratory-evolved clones,…
View article: A diagnostic host response biosignature for COVID-19 from RNA profiling of nasal swabs and blood
A diagnostic host response biosignature for COVID-19 from RNA profiling of nasal swabs and blood Open
SARS-CoV-2 infection elicits a distinct host response in nasal swabs and blood that can be used to diagnose COVID-19.
View article: Deep Learning Models May Spuriously Classify Covid-19 from X-ray Images\n Based on Confounders
Deep Learning Models May Spuriously Classify Covid-19 from X-ray Images\n Based on Confounders Open
Identifying who is infected with the Covid-19 virus is critical for\ncontrolling its spread. X-ray machines are widely available worldwide and can\nquickly provide images that can be used for diagnosis. A number of recent\nstudies claim it…
View article: Deep Learning Models May Spuriously Classify Covid-19 from X-ray Images Based on Confounders
Deep Learning Models May Spuriously Classify Covid-19 from X-ray Images Based on Confounders Open
Identifying who is infected with the Covid-19 virus is critical for controlling its spread. X-ray machines are widely available worldwide and can quickly provide images that can be used for diagnosis. A number of recent studies claim it ma…
View article: Discovery of a Generalization Gap of Convolutional Neural Networks on COVID-19 X-Rays Classification
Discovery of a Generalization Gap of Convolutional Neural Networks on COVID-19 X-Rays Classification Open
A number of recent papers have shown experimental evidence that suggests it is possible to build highly accurate deep neural network models to detect COVID-19 from chest X-ray images. In this paper, we show that good generalization to unse…
View article: SARS-CoV-2 seroprevalence and neutralizing activity in donor and patient blood
SARS-CoV-2 seroprevalence and neutralizing activity in donor and patient blood Open
View article: Evaluation of SARS-CoV-2 serology assays reveals a range of test performance
Evaluation of SARS-CoV-2 serology assays reveals a range of test performance Open
View article: Magnitude and Kinetics of Anti–Severe Acute Respiratory Syndrome Coronavirus 2 Antibody Responses and Their Relationship to Disease Severity
Magnitude and Kinetics of Anti–Severe Acute Respiratory Syndrome Coronavirus 2 Antibody Responses and Their Relationship to Disease Severity Open
Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can be detected indirectly by measuring the host immune response. For some viruses, antibody concentrations correlate with host protection and viral neutrali…
View article: Magnitude and kinetics of anti-SARS-CoV-2 antibody responses and their relationship to disease severity
Magnitude and kinetics of anti-SARS-CoV-2 antibody responses and their relationship to disease severity Open
Background SARS-CoV-2 infection can be detected indirectly by measuring the host immune response. Anti-viral antibody concentrations generally correlate with host protection and viral neutralization, but in rare cases, antibodies can promo…
View article: SARS-CoV-2 seroprevalence and neutralizing activity in donor and patient blood from the San Francisco Bay Area
SARS-CoV-2 seroprevalence and neutralizing activity in donor and patient blood from the San Francisco Bay Area Open
We report very low SARS-CoV-2 seroprevalence in two San Francisco Bay Area populations. Seropositivity was 0.26% in 387 hospitalized patients admitted for non-respiratory indications and 0.1% in 1,000 blood donors. We additionally describe…
View article: Finding COVID-19 from Chest X-rays using Deep Learning on a Small Dataset
Finding COVID-19 from Chest X-rays using Deep Learning on a Small Dataset Open
Testing for COVID-19 has been unable to keep up with the demand. Further, the false negative rate is projected to be as high as 30% and test results can take some time to obtain. X-ray machines are widely available and provide images for d…
View article: Test performance evaluation of SARS-CoV-2 serological assays
Test performance evaluation of SARS-CoV-2 serological assays Open
Background Serological tests are crucial tools for assessments of SARS-CoV-2 exposure, infection and potential immunity. Their appropriate use and interpretation require accurate assay performance data. Method We conducted an evaluation of…
View article: Finding COVID-19 from Chest X-rays using Deep Learning on a Small Dataset
Finding COVID-19 from Chest X-rays using Deep Learning on a Small Dataset Open
esting for COVID-19 has been unable to keep up with the demand. Further, the false negative rate is projected to be as high as 30\ and test results can take some time to obtain. X-ray machines are widely available and provide images for di…
View article: Pan-active imidazolopiperazine antimalarials target the Plasmodium falciparum intracellular secretory pathway
Pan-active imidazolopiperazine antimalarials target the Plasmodium falciparum intracellular secretory pathway Open
View article: Finding COVID-19 from Chest X-rays using Deep Learning on a Small Dataset
Finding COVID-19 from Chest X-rays using Deep Learning on a Small Dataset Open
Testing for COVID-19 has been unable to keep up with the demand. Further, the false negative rate is projected to be as high as 30% and test results can take some time to obtain. X-ray machines are widely available and provide images for d…
View article: Finding COVID-19 from Chest X-rays using Deep Learning on a Small Dataset
Finding COVID-19 from Chest X-rays using Deep Learning on a Small Dataset Open
Testing for COVID-19 has been unable to keep up with the demand. Further, the false negative rate is projected to be as high as 30% and test results can take some time to obtain. X-ray machines are widely available and provide images for d…
View article: Finding COVID-19 from Chest X-rays using Deep Learning on a Small Dataset
Finding COVID-19 from Chest X-rays using Deep Learning on a Small Dataset Open
Testing for COVID-19 has been unable to keep up with the demand. Further, the false negative rate is projected to be as high as 30% and test results can take some time to obtain. X-ray machines are widely available and provide images for d…
View article: Finding Covid-19 from Chest X-rays using Deep Learning on a Small Dataset
Finding Covid-19 from Chest X-rays using Deep Learning on a Small Dataset Open
Testing for COVID-19 has been unable to keep up with the demand. Further, the false negative rate is projected to be as high as 30% and test results can take some time to obtain. X-ray machines are widely available and provide images for d…
View article: Pan-active imidazolopiperazine antimalarials target the<i>Plasmodium falciparum</i>intracellular secretory pathway
Pan-active imidazolopiperazine antimalarials target the<i>Plasmodium falciparum</i>intracellular secretory pathway Open
A bstract One of the most promising new compound classes in clinical development for the treatment of malaria is the imidazolopiperazines (IZPs) class. Human trials have demonstrated that members of the IZP series, which includes KAF156 (G…
View article: Two inhibitors of yeast plasma membrane ATPase 1 (ScPma1p): toward the development of novel antifungal therapies
Two inhibitors of yeast plasma membrane ATPase 1 (ScPma1p): toward the development of novel antifungal therapies Open