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Articles 1 - 30 of 119
Full-Text Articles in Medicine and Health Sciences
A Mathematical Modeling Study On Hdv Rna, Alt, And Hbsag Dynamics Reveals Dual Mechanisms Of Peginterferon-Lambda., Adquate Mhlanga, Ohad Etzion, Harel Dahari
A Mathematical Modeling Study On Hdv Rna, Alt, And Hbsag Dynamics Reveals Dual Mechanisms Of Peginterferon-Lambda., Adquate Mhlanga, Ohad Etzion, Harel Dahari
Biology and Medicine Through Mathematics Conference
No abstract provided.
Benefit Of Medication Reconciliation Practices On Patient Health Outcomes In A Healthcare Setting, Helen Harris, David Petrulis, Lauren Trepp, Bryan Chong, Jillian Haas, David Chan, Laura Ellwein Fix
Benefit Of Medication Reconciliation Practices On Patient Health Outcomes In A Healthcare Setting, Helen Harris, David Petrulis, Lauren Trepp, Bryan Chong, Jillian Haas, David Chan, Laura Ellwein Fix
Biology and Medicine Through Mathematics Conference
No abstract provided.
A Histological Data-Driven Analysis Of The Hypoxic Microenvironment Of Preclinical Murine Bladder Tumors, Awino Maureiq E. Ojwang'
A Histological Data-Driven Analysis Of The Hypoxic Microenvironment Of Preclinical Murine Bladder Tumors, Awino Maureiq E. Ojwang'
Biology and Medicine Through Mathematics Conference
No abstract provided.
Modeling And Control Of Drug Resistance In Cancer Dynamics, James Greene
Modeling And Control Of Drug Resistance In Cancer Dynamics, James Greene
Biology and Medicine Through Mathematics Conference
No abstract provided.
Identifiability Analysis And Model Reduction For Soft Tissue Models, Mansoor A. Haider
Identifiability Analysis And Model Reduction For Soft Tissue Models, Mansoor A. Haider
Biology and Medicine Through Mathematics Conference
No abstract provided.
Mathematical Modeling Suggests Pathways Of Systemic Dissemination Of Mycobacterium Tuberculosis In Mice, Vitaly V. Ganusov
Mathematical Modeling Suggests Pathways Of Systemic Dissemination Of Mycobacterium Tuberculosis In Mice, Vitaly V. Ganusov
Biology and Medicine Through Mathematics Conference
No abstract provided.
Modeling Interactions Between Platelet-Like Particles And Fibrin Matrix During Polymerization And Ultrasound Stimulation In Wound Healing Applications, Julia Sanger, Ashley C. Brown, Marie Muller, Mansoor A. Haider
Modeling Interactions Between Platelet-Like Particles And Fibrin Matrix During Polymerization And Ultrasound Stimulation In Wound Healing Applications, Julia Sanger, Ashley C. Brown, Marie Muller, Mansoor A. Haider
Biology and Medicine Through Mathematics Conference
No abstract provided.
Sperm-Egg Interaction For Fertilization Success, Prajakta P. Bedekar
Sperm-Egg Interaction For Fertilization Success, Prajakta P. Bedekar
Biology and Medicine Through Mathematics Conference
No abstract provided.
Modeling Synergistic Effects Of Integrin And Tgf-Beta Signaling In Epithelial Mesenchymal Transition, Prerak Thakkar
Modeling Synergistic Effects Of Integrin And Tgf-Beta Signaling In Epithelial Mesenchymal Transition, Prerak Thakkar
Biology and Medicine Through Mathematics Conference
No abstract provided.
A Random Differential Equation Model To Estimate Treatment Sensitivity In Synthetic And In Vitro Tumor Growth Data, Natalie Meacham
A Random Differential Equation Model To Estimate Treatment Sensitivity In Synthetic And In Vitro Tumor Growth Data, Natalie Meacham
Biology and Medicine Through Mathematics Conference
No abstract provided.
Mathematical Modeling Of Immune Response To Sars-Cov-2, Hwayeon Ryu
Mathematical Modeling Of Immune Response To Sars-Cov-2, Hwayeon Ryu
Biology and Medicine Through Mathematics Conference
No abstract provided.
Topological Data Analysis Of Molecular Dynamics Simulations Of Monoclonal Antibodies, Melinda Kleczynski, Christina Bergonzo, Anthony Kearsley
Topological Data Analysis Of Molecular Dynamics Simulations Of Monoclonal Antibodies, Melinda Kleczynski, Christina Bergonzo, Anthony Kearsley
Biology and Medicine Through Mathematics Conference
No abstract provided.
In Silico Analysis Of C-Type Lectins As Co-Infection Receptors Of Dengue And Chikungunya Viruses In Aedes Aegypti, Munawir Sazali, R. C. Hidayat Soesilohadi, Nastiti Wijayanti, Tri Wibawa, Arif Nur Muhammad Ansori
In Silico Analysis Of C-Type Lectins As Co-Infection Receptors Of Dengue And Chikungunya Viruses In Aedes Aegypti, Munawir Sazali, R. C. Hidayat Soesilohadi, Nastiti Wijayanti, Tri Wibawa, Arif Nur Muhammad Ansori
Makara Journal of Science
Aedes aegypti is a primer vector of dengue virus (DENV) and chikungunya virus (CHIKV). The susceptibility of mosquitoes to DENV and CHIKV depends on their recognition receptor of pathogens. C-type lectins (CTLs) are an important mediator of virus infection in A. aegypti. This study aims to identify potential receptors and determine the binding affinity between ligand–receptor interaction, CTLs and virus envelopes (DENV-1, 2, 3, and 4 and CHIKV) interaction based on in silico analysis. Sample sequences were obtained from GenBank (NCBI), and 10 CTLs were acquired from VectorBase. Homology modeling based on a minimum standard of 20% was processed …
Identifying Patterns For Neurological Disabilities By Integrating Discrete Wavelet Transform And Visualization, Soo Yeon Ji, Sampath Jayarathna, Anne M. Perrotti, Katrina Kardiasmenos, Dong Hyun Jeong
Identifying Patterns For Neurological Disabilities By Integrating Discrete Wavelet Transform And Visualization, Soo Yeon Ji, Sampath Jayarathna, Anne M. Perrotti, Katrina Kardiasmenos, Dong Hyun Jeong
Computer Science Faculty Publications
Neurological disabilities cause diverse health and mental challenges, impacting quality of life and imposing financial burdens on both the individuals diagnosed with these conditions and their caregivers. Abnormal brain activity, stemming from malfunctions in the human nervous system, characterizes neurological disorders. Therefore, the early identification of these abnormalities is crucial for devising suitable treatments and interventions aimed at promoting and sustaining quality of life. Electroencephalogram (EEG), a non-invasive method for monitoring brain activity, is frequently employed to detect abnormal brain activity in neurological and mental disorders. This study introduces an approach that extends the understanding and identification of neurological disabilities …
Quercetin As An Anticancer Candidate For Glioblastoma Multiforme By Targeting Akt1, Mmp9, Abcb1, And Vegfa: An In Silico Study, Muhammad Hermawan Widyananda, Setyaki Kevin Pratama, Arif Nur Muhammad Ansori, Yulanda Antonius, Viol Dhea Kharisma, Ahmad Affan Ali Murtadlo, Vikash Jakhmola, Maksim Rebezov, Mars Khayrullin, Marina Derkho, Emdad Ullah, Raden Joko Kuncoroningrat Susilo, Suhailah Hayaza, Alexander Patera Nugraha, Annise Proboningrat, Amaq Fadholly, Mada Triandala Sibero, Rahadian Zainul
Quercetin As An Anticancer Candidate For Glioblastoma Multiforme By Targeting Akt1, Mmp9, Abcb1, And Vegfa: An In Silico Study, Muhammad Hermawan Widyananda, Setyaki Kevin Pratama, Arif Nur Muhammad Ansori, Yulanda Antonius, Viol Dhea Kharisma, Ahmad Affan Ali Murtadlo, Vikash Jakhmola, Maksim Rebezov, Mars Khayrullin, Marina Derkho, Emdad Ullah, Raden Joko Kuncoroningrat Susilo, Suhailah Hayaza, Alexander Patera Nugraha, Annise Proboningrat, Amaq Fadholly, Mada Triandala Sibero, Rahadian Zainul
Karbala International Journal of Modern Science
Quercetin, a natural compound present in various fruits and vegetables, shows promise as a potential inhibitor for glioblastoma multiforme (GBM) development. This study aims to examine the anti-GBM potential of Quercetin. The protein target of Quercetin is identified and analyzed using databases such as NCBI, SEA, CTD, and STRING. Protein-protein interaction (PPI) and functional annotation are carried out based on the obtained target proteins. Molecular docking and dynamics simulations are employed using AutoDock Vina and WebGro tools to analyze the interaction between Quercetin and its target proteins. The prediction of protein targets reveals that Quercetin directly targets four proteins associated …
Stochastic Gradient Descent Method For A Parameter Identification Problem In Elasticity Imaging, Basca Jadamba
Stochastic Gradient Descent Method For A Parameter Identification Problem In Elasticity Imaging, Basca Jadamba
Biology and Medicine Through Mathematics Conference
No abstract provided.
Mathematical Modeling Of Immune Response To Sars-Cov-2, Hwayeon Ryu
Mathematical Modeling Of Immune Response To Sars-Cov-2, Hwayeon Ryu
Biology and Medicine Through Mathematics Conference
No abstract provided.
Modeling The Immune Response To Immunotherapy And Triple Negative Breast Cancer In Mice, Dayton J. Syme, Angelica Davenport, Yun Lu, Anna G. Sorace, Nicholas G. Cogan
Modeling The Immune Response To Immunotherapy And Triple Negative Breast Cancer In Mice, Dayton J. Syme, Angelica Davenport, Yun Lu, Anna G. Sorace, Nicholas G. Cogan
Biology and Medicine Through Mathematics Conference
No abstract provided.
Chemoattractant Distribution In Complex Geometry Impacts The Trajectory Of Clustered Cell Migration, Naghmeh Akhavan
Chemoattractant Distribution In Complex Geometry Impacts The Trajectory Of Clustered Cell Migration, Naghmeh Akhavan
Biology and Medicine Through Mathematics Conference
No abstract provided.
Pk/Pd Modeling Coupled With A Phenotype-Structured Population Model For Reducing Drug Resistance, Lifeng Han
Pk/Pd Modeling Coupled With A Phenotype-Structured Population Model For Reducing Drug Resistance, Lifeng Han
Biology and Medicine Through Mathematics Conference
No abstract provided.
Modeling Epithelial-Mesenchymal Transition In A 3d Multicellular Model Of Tgf-Β1 Signaling, Kristin Kim, Chris Lemmon
Modeling Epithelial-Mesenchymal Transition In A 3d Multicellular Model Of Tgf-Β1 Signaling, Kristin Kim, Chris Lemmon
Biology and Medicine Through Mathematics Conference
No abstract provided.
A Machine Learning Approach For Predicting Clinical Trial Patient Enrollment In Drug Development Portfolio Demand Planning, Ahmed Shoieb
A Machine Learning Approach For Predicting Clinical Trial Patient Enrollment In Drug Development Portfolio Demand Planning, Ahmed Shoieb
Masters Theses
One of the biggest challenges the clinical research industry currently faces is the accurate forecasting of patient enrollment (namely if and when a clinical trial will achieve full enrollment), as the stochastic behavior of enrollment can significantly contribute to delays in the development of new drugs, increases in duration and costs of clinical trials, and the over- or under- estimation of clinical supply. This study proposes a Machine Learning model using a Fully Convolutional Network (FCN) that is trained on a dataset of 100,000 patient enrollment data points including patient age, patient gender, patient disease, investigational product, study phase, blinded …
Prediction Of Rapid Early Progression And Survival Risk With Pre-Radiation Mri In Who Grade 4 Glioma Patients, Walia Farzana, Mustafa M. Basree, Norou Diawara, Zeina Shboul, Sagel Dubey, Marie M. Lockheart, Mohamed Hamza, Joshua D. Palmer, Khan Iftekharuddin
Prediction Of Rapid Early Progression And Survival Risk With Pre-Radiation Mri In Who Grade 4 Glioma Patients, Walia Farzana, Mustafa M. Basree, Norou Diawara, Zeina Shboul, Sagel Dubey, Marie M. Lockheart, Mohamed Hamza, Joshua D. Palmer, Khan Iftekharuddin
Electrical & Computer Engineering Faculty Publications
Rapid early progression (REP) has been defined as increased nodular enhancement at the border of the resection cavity, the appearance of new lesions outside the resection cavity, or increased enhancement of the residual disease after surgery and before radiation. Patients with REP have worse survival compared to patients without REP (non-REP). Therefore, a reliable method for differentiating REP from non-REP is hypothesized to assist in personlized treatment planning. A potential approach is to use the radiomics and fractal texture features extracted from brain tumors to characterize morphological and physiological properties. We propose a random sampling-based ensemble classification model. The proposed …
Medical Racism: Comparing Prenatal Care Across Races In The United States, Rubina Cheema
Medical Racism: Comparing Prenatal Care Across Races In The United States, Rubina Cheema
Student Research
Prenatal care describes any care a woman receives during her pregnancy. It is intended to keep both the mother and the child healthy and also to reduce the risk of complications during and after birth. This care is especially important for women with high-risk factors so that doctors and nurses are able to monitor their health and the health of their baby during the duration of their pregnancy. For prenatal care to be most effective, it is imperative to begin prenatal care within the first trimester of a woman's pregnancy. However, in the United States, medical racism creates a major …
Artificial Intelligence In The Medical Field: Medical Review Sentiment Analysis, Nicholas Podlesak
Artificial Intelligence In The Medical Field: Medical Review Sentiment Analysis, Nicholas Podlesak
Honors Capstones
In this research project, natural language processing techniques’ ability to accurately classify medical text was measured to reinforce the relevance of artificial intelligence in the medical field. Sentiment analyses (analyses to determine whether the text was positive or negative) were performed on the prescription drug reviews in an open-source dataset using four different models: lexical, a neural network, a support vector machine, and a logistic regression model. Each model’s effectiveness was gauged by its ability to correctly classify unlabeled drug reviews (i.e., a percentage representing accuracy). The machine learning models were able to accurately classify the text, while the lexical …
Application In Medicine: Has Artificial Intelligence Stood The Test Of Time, Mir Ibrahim Sajid, Shaheer Ahmed, Usama Waqar, Javeria Tariq, Mohsin Chundrigar, Samira Shabbir Balouch, Sajid Abaidullah
Application In Medicine: Has Artificial Intelligence Stood The Test Of Time, Mir Ibrahim Sajid, Shaheer Ahmed, Usama Waqar, Javeria Tariq, Mohsin Chundrigar, Samira Shabbir Balouch, Sajid Abaidullah
Medical College Documents
Artificial intelligence (AI) has proven time and time again to be a game-changer innovation in every walk of life, including medicine. Introduced by Dr. Gunn in 1976 to accurately diagnose acute abdominal pain and list potential differentials, AI has since come a long way. In particular, AI has been aiding in radiological diagnoses with good sensitivity and specificity by using machine learning algorithms. With the coronavirus disease 2019 pandemic, AI has proven to be more than just a tool to facilitate healthcare workers in decision making and limiting physician-patient contact during the pandemic. It has guided governments and key policymakers …
Modeling Acute And Chronic Vascular Adaptations To A Major Arterial Occlusion, Erin O. Zhao
Modeling Acute And Chronic Vascular Adaptations To A Major Arterial Occlusion, Erin O. Zhao
Biology and Medicine Through Mathematics Conference
No abstract provided.
Mechanical Parameters Fitting For Layer-Reduced Umbilical Arteries Used For Grafting, Kun Gou
Mechanical Parameters Fitting For Layer-Reduced Umbilical Arteries Used For Grafting, Kun Gou
Biology and Medicine Through Mathematics Conference
No abstract provided.
Mathematical Model Of Triple-Negative Breast Cancer In Response To Combination Chemotherapies, Angelica Davenport, Yun Lu, Carlos Gallegos, Adriana Massicano, Katherine Heinzman, Patrick Song, Anna Sorace, Nick Cogan
Mathematical Model Of Triple-Negative Breast Cancer In Response To Combination Chemotherapies, Angelica Davenport, Yun Lu, Carlos Gallegos, Adriana Massicano, Katherine Heinzman, Patrick Song, Anna Sorace, Nick Cogan
Biology and Medicine Through Mathematics Conference
No abstract provided.
A Mathematical Model Of Microtubule Assembly And Polarity In Dendrites, Anna Nelson
A Mathematical Model Of Microtubule Assembly And Polarity In Dendrites, Anna Nelson
Biology and Medicine Through Mathematics Conference
No abstract provided.