A5048775652- Lung Cancer Treatments and Mutations
- Cancer Immunotherapy and Biomarkers
- Cancer Genomics and Diagnostics
- Topic Modeling
- Artificial Intelligence in Healthcare and Education
- Machine Learning in Healthcare
- Lung Cancer Diagnosis and Treatment
- Lung Cancer Research Studies
- Pancreatic and Hepatic Oncology Research
- Emergency and Acute Care Studies
- Chromosomal and Genetic Variations
- Genomic variations and chromosomal abnormalities
- Congenital heart defects research
- Natural Language Processing Techniques
- Child and Adolescent Health
- Childhood Cancer Survivors' Quality of Life
New York University
2023-2024
University of Pennsylvania
2020-2021
Abstract Purpose: The role of plasma-based tumor mutation burden (pTMB) in predicting response to pembrolizumab-based first-line standard-of-care therapy for metastatic non–small cell lung cancer (mNSCLC) has not been explored. Experimental Design: A 500-gene next-generation sequencing panel was used assess pTMB. Sixty-six patients with newly diagnosed mNSCLC starting therapy, either alone or combination chemotherapy, were enrolled (Clinicaltrial.gov identifier: NCT03047616). Response...
PURPOSE Although the majority of patients with metastatic non–small-cell lung cancer (mNSCLC) lacking a detectable targetable mutation will receive pembrolizumab-based therapy in frontline setting, predicting which experience durable clinical benefit (DCB) remains challenging. MATERIALS AND METHODS Patients mNSCLC receiving pembrolizumab monotherapy or combination chemotherapy underwent 74-gene next-generation sequencing panel on blood samples obtained at baseline and 9 weeks. The change...
Abstract Importance Large language models (LLMs) are crucial for medical tasks. Ensuring their reliability is vital to avoid false results. Our study assesses two state-of-the-art LLMs (ChatGPT and LlaMA-2) extracting clinical information, focusing on cognitive tests like MMSE CDR. Objective Evaluate ChatGPT LlaMA-2 performance in CDR scores, including associated dates. Methods data consisted of 135,307 notes (Jan 12th, 2010 May 24th, 2023) mentioning MMSE, CDR, or MoCA. After applying...
Ensuring reliability of Large Language Models (LLMs) in clinical tasks is crucial. Our study assesses two state-of-the-art LLMs (ChatGPT and LlaMA-2) for extracting information, focusing on cognitive tests like MMSE CDR. data consisted 135,307 notes (Jan 12th, 2010 to May 24th, 2023) mentioning MMSE, CDR, or MoCA. After applying inclusion criteria 34,465 remained, which 765 underwent ChatGPT (GPT-4) LlaMA-2, 22 experts reviewed the responses. successfully extracted CDR instances with dates...
Abstract The most prevalent microdeletion in humans occurs at 22q11.2, a region rich chromosome-specific low copy repeats (LCR22s). structure of this has defied elucidation due to its size, regional complexity, and haplotype diversity, is not well represented the human genome reference. Most individuals with 22q11.2 deletion syndrome (22q11.2DS) carry de novo hemizygous ~ 3 Mbp occurring by non-allelic homologous recombination (NAHR) mediated LCR22s. In study, optical mapping been used...
Abstract Background High rates of posthospitalization errors are observed in children with medical complexity (CMC). Poor parent comprehension and adherence to complex discharge instructions can contribute errors. Pediatrician views on common barriers facilitators understudied. Objective To examine pediatrician perspectives experienced by parents inpatient for CMC. Design, Settings, Participants We conducted a qualitative, descriptive study attending pediatricians ( n = 20) caring CMC...
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Abstract Background Large language models (LLMs) provide powerful natural processing capabilities in medical and clinical tasks. Evaluating LLM performance is crucial due to potential false results. In this study, we assessed ChatGPT Llama2, two state‐of‐the‐art LLMs, extracting information from notes, focusing on cognitive tests, specifically the Mini Mental State Exam (MMSE) Cognitive Dementia Rating (CDR). Method We compiled a dataset consisting of 765 notes mentioning MMSE CDR. 22...
<p>Overall response to pembrolizumab monotherapy (n=31, left) and combination therapy (n=34*, right).</p>
<p>Mutations Analyzed</p>
<p>Development and validation of a plasma-based panel for mutation detection assessment TMB.</p>
<p>Overall response to pembrolizumab monotherapy (n=31, left) and combination therapy (n=34*, right).</p>
<p>pTMBand PD-L1 expression levels.</p>
<div>AbstractPurpose:<p>The role of plasma-based tumor mutation burden (pTMB) in predicting response to pembrolizumab-based first-line standard-of-care therapy for metastatic non–small cell lung cancer (mNSCLC) has not been explored.</p>Experimental Design:<p>A 500-gene next-generation sequencing panel was used assess pTMB. Sixty-six patients with newly diagnosed mNSCLC starting therapy, either alone or combination chemotherapy, were enrolled (Clinicaltrial.gov...
<div>AbstractPurpose:<p>The role of plasma-based tumor mutation burden (pTMB) in predicting response to pembrolizumab-based first-line standard-of-care therapy for metastatic non–small cell lung cancer (mNSCLC) has not been explored.</p>Experimental Design:<p>A 500-gene next-generation sequencing panel was used assess pTMB. Sixty-six patients with newly diagnosed mNSCLC starting therapy, either alone or combination chemotherapy, were enrolled (Clinicaltrial.gov...
<p>pTMBand PD-L1 expression levels.</p>
<p>Development and validation of a plasma-based panel for mutation detection assessment TMB.</p>
<p>Mutations Analyzed</p>