Kathleen A. Miller

ORCID: 0000-0003-0352-470X
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About
Contact & Profiles
Research Areas
  • Reproductive Biology and Fertility
  • Assisted Reproductive Technology and Twin Pregnancy
  • Prenatal Screening and Diagnostics
  • Ovarian function and disorders
  • Reproductive Health and Technologies
  • Genomic variations and chromosomal abnormalities
  • Sperm and Testicular Function
  • Endometriosis Research and Treatment
  • Reproductive System and Pregnancy
  • Molecular Biology Techniques and Applications
  • Animal Genetics and Reproduction
  • Genetic Syndromes and Imprinting
  • Demographic Trends and Gender Preferences
  • Irish and British Studies
  • Acute Ischemic Stroke Management
  • CRISPR and Genetic Engineering
  • Gynecological conditions and treatments
  • Pluripotent Stem Cells Research
  • Artificial Intelligence in Healthcare and Education
  • Cancer Genomics and Diagnostics
  • Reproductive Health and Contraception
  • Chromosomal and Genetic Variations
  • Gene expression and cancer classification
  • Mechanical Circulatory Support Devices
  • Law, AI, and Intellectual Property

Our Lady of Lourdes Medical Center
2022-2024

Reproductive Biology Associates
2015-2023

New Hope Fertility Center
2023

Virtua Health
2022-2023

Florida Urology Associates
2022

Texas Children's Hospital
2016

Reproductive Medicine Associates of New Jersey
2000-2009

Johnson University
2007-2009

Reproductive Medicine Associates of New York
2003-2008

Weatherford College
2008

Identifying the genes responsible for human diseases requires combining information about gene position with clues biological function. The recent availability of whole-genome data sets RNA and protein expression provides powerful new sources functional insight. Here we illustrate how such can expedite disease-gene discovery, by using them to identify causing Leigh syndrome, French-Canadian type (LSFC, Online Mendelian Inheritance in Man no. 220111), a cytochrome c oxidase deficiency that...

10.1073/pnas.242716699 article EN Proceedings of the National Academy of Sciences 2003-01-14

To determine whether male age influences embryo development and reproductive potential in assisted technology cycles.Retrospective cohort analysis.Private IVF center.One thousand twenty-three partners participating anonymous oocyte donation cycles.Infertile couples undergoing 1,023 cycles.Live birth rate.A significant increase pregnancy loss, decrease live rate, blastocyst formation rate were noted men >50 years of age. There was no difference implantation or early through the cleavage stage...

10.1016/j.fertnstert.2007.06.009 article EN publisher-specific-oa Fertility and Sterility 2007-09-05

ObjectiveTo perform a series of analyses characterizing an artificial intelligence (AI) model for ranking blastocyst-stage embryos. The primary objective was to evaluate the benefit predicting clinical pregnancy, whereas secondary identify limitations that may impact use.DesignRetrospective study.SettingConsortium 11 assisted reproductive technology centers in United States.Patient(s)Static images 5,923 transferred blastocysts and 2,614 nontransferred aneuploid...

10.1016/j.fertnstert.2021.11.022 article EN cc-by-nc-nd Fertility and Sterility 2022-01-05

Preimplantation genetic testing commonly employs simplistic copy-number analyses to screen for aneuploidy in blastocyst trophectoderm biopsies. Interpreting intermediate copy number alone as evidence of mosaicism has led suboptimal estimation its prevalence. Because originates from mitotic nondisjunction, utilizing SNP microarray technology identify the cell-division origins might provide a more accurate The present study develops and validates method determining origin human by using both...

10.1016/j.ajhg.2023.03.003 article EN cc-by The American Journal of Human Genetics 2023-03-27

Assessing fertilized human embryos is crucial for in vitro fertilization, a task being revolutionized by artificial intelligence. Existing models used embryo quality assessment and ploidy detection could be significantly improved effectively utilizing time-lapse imaging to identify critical developmental time points maximizing prediction accuracy. Addressing this, we develop compare various status across distinct development stages. We present BELA, state-of-the-art model that surpasses...

10.1038/s41467-024-51823-7 article EN cc-by-nc-nd Nature Communications 2024-09-05

The COVID-19 pandemic has posed unique concerns and potential risks to women now pregnant or considering childbearing. Although no professional societies have issued recommendations that avoid conception at this time, several organizations recommended a moratorium on infertility services including both medically assisted reproduction reproductive technology shortly after the World Health Organization declared infection be pandemic. Reasons cited for undertaking these extraordinary measures...

10.1097/grh.0000000000000043 article EN cc-by-nd Global Reproductive Health 2020-01-01

Differential CYP1A1 inducibility, reflecting variations in aromatic hydrocarbon receptor (AHR) affinity among inbred mouse strains, is an important determinant of environmental toxicity. We took advantage the Ahr polymorphism C57BL/6 and DBA/2 mice to develop oligonucleotide-hybridization screening approach for rapid identification DNA sequence differences between alleles. Oligonucleotides containing single-base changes at polymorphic sites were immobilized on a solid support hybridized with...

10.1289/ehp.106-1533118 article EN public-domain Environmental Health Perspectives 1998-07-01

Abstract Assessing fertilized human embryos is crucial for in vitro-fertilization (IVF), a task being revolutionized by artificial intelligence and deep learning. Existing models used embryo quality assessment chromosomal abnormality (ploidy) detection could be significantly improved effectively utilizing time-lapse imaging to identify critical developmental time points maximizing prediction accuracy. Addressing this, we developed compared various ploidy status across distinct development...

10.1101/2023.08.31.555741 preprint EN bioRxiv (Cold Spring Harbor Laboratory) 2023-09-02
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