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Methods of Clinical Epidemiology

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This book provides an introduction to the common research methodology specific to clinical epidemiology for both students and researchers. The goal of the book is to fill the gap left by texts that concentrate on public health epidemiology and focuses on what is not covered well in such publications

. The four sections of the book cover methods that have not previously been brought together in one volume and serve as a second level textbook of clinical epidemiology methods. Some of the most important topics included in this volume are: clinical agreement in quantitative measurements, interpreta

tion of diagnostic tests, sample size considerations, modelling time-to-event data and meta-analysis. The book will be useful for clinical researchers as well as for postgraduate students in clinical epidemiology. In this second edition, sections related to modeling of binary outcomes and research s

ynthesis methods have been extensively updated. Suhail Doi is associate professor of clinical epidemiology at the University of Queensland. He is involved in teaching, student supervision, curriculum development and research. He has published widely and his interest lies in research that addresse

s unanswered questions in patient care as well as questions related to methods of research design and analysis used in medicine. Thus his research focuses on patient care topics such as epidemiology, prognosis and treatments of disease as well as methodology especially that related to meta-analysis.

He is the co-author of the Doi-Thalib method for meta-analysis which was introduced in 2008 as an alternative to the random effects model. Gail Williams is professor of international health statistics at the University of Queensland. She has had long involvement in curriculum development and teachi

ng in graduate programs in biostatistics and epidemiology, as well as consulting in clinical medicine and public health. Her specific areas of expertise include design and analysis of longitudinal studies, clinical and field intervention trials, survey design, and mathematical modelling. The focus o

f her applied research has been maternal and child health, a range of infectious diseases, and skin cancer. Her methodological areas of interest lie in statistical and mathematical modelling and approaches to dealing with attrition in longitudinal studies.

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Printed Antennas: Theory and Design

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Dr. Binod Kumar Kanaujia has been a Professor at the School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi since August 2016. Before joining Jawaharlal Nehru University, he was in the Department of Electronics & Communication Engineering in Ambedkar Institute of Ad

vanced Communication Technologies & Research, Delhi as a Professor from February 2011 and Associate Professor between 2008-2011. Prior to his career in academia, Dr. Kanaujia had worked as Executive Engineer in the R&D division of M/s UPTRON India Ltd. Dr. Surendra Kumar Gupta is a Senior Faculty Me

mber with Department of Electronics Engineering, Ambedkar Institute of Technology, Government of Delhi, India since 2002. He has authored / co-authored around 20 research papers in International Journals / Conferences. His research interests include Computer Aided Design, Wireless Communication and

Micro-strip Antenna. He is a reviewer for several journals of National / International repute and Editorial Board Member of Insight-Communication Journal. He is life member of Indian Society of Technical Education, India and Associate Member of Institute of Engineers, India. Dr. Jugul Kishor is curr

ently working as Associate Professor at the JIMS Engineering Management Technical Campus, Greater Noida, India. His research interests include Design and Modelling of Microstrip and Dielectric Resonator based devices and Metamaterial based antenna including Circularly Polarized Antennas.　Dr. Deepak

Gangwar is working as Associate Professor at Bharati Vidyapeeth’s College of Engineering, New Delhi, India. His research areas of interest include Analysis and Design of Metamaterial based Antennas, Ultra-Wideband Antennas, Metamaterial Filters and Frequency Selective Surfaces, Meta surfaces and RCS

reduction.

An Integrated Approach For Uncovering Novel DNA Methylation Biomarkers For Non-small Cell Lung Carcinoma

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Introduction - Lung cancer is one of primal and ubiquitous cause of cancer related fatalities in the world. Leading cause of these fatalities is non-small cell lung cancer (NSCLC) with a proportion of 85%. The major subtypes of NSCLC are Lung Adenocarcinoma (LUAD) and Lung Small Cell Carcinoma (LUS

C). Early-stage surgical detection and removal of tumor offers a favorable prognosis and better survival rates. However, a major portion of 75% subjects have stage III/IV at the time of diagnosis and despite advanced major developments in oncology survival rates remain poor. Carcinogens produce wide

spread DNA methylation changes within cells. These changes are characterized by globally hyper or hypo methylated regions around CpG islands, many of these changes occur early in tumorigenesis and are highly prevalent across a tumor type.Structure - This research work took advantage of publicly avai

lable methylation profiling resources and relevant comorbidities for lung cancer patients extracted from meta-analysis of scientific review and journal available at PubMed and CNKI search which were combined systematically to explore effective DNA methylation markers for NSCLC. We also tried to iden

tify common CpG loci between Caucasian, Black and Asian racial groups for identifying ubiquitous candidate genes thoroughly. Statistical analysis and GO ontology were also conducted to explore associated novel biomarkers. These novel findings could facilitate design of accurate diagnostic panel for

practical clinical relevance.Methodology - DNA methylation profiles were extracted from TCGA for 418 LUAD and 370 LUSC tissue samples from patients compared with 32 and 42 non-malignant ones respectively. Standard pipeline was conducted to discover significant differentially methylated sites as prim

ary biomarkers. Secondary biomarkers were extracted by incorporating genes associated with comorbidities from meta-analysis of research articles. Concordant candidates were utilized for NSCLC relevant biomarker candidates. Gene ontology annotations were used to calculate gene-pair distance matrix fo

r all candidate biomarkers. Clustering algorithms were utilized to categorize candidate genes into different functional groups using the gene distance matrix. There were 35 CpG loci identified by comparing TCGA training cohort with GEO testing cohort from these functional groups, and 4 gene-based pa

nel was devised after finding highly discriminatory diagnostic panel through combinatorial validation of each functional cluster.Results – To evaluate the gene panel for NSCLC, the methylation levels of SCT(Secritin), FOXD3(Forkhead Box D3), TRIM58(Tripartite Motif Containing 58) and TAC1(Tachikinin

1) were tested. Individually each gene showed significant methylation difference between LUAD and LUSC training cohort. Combined 4-gene panel AUC, sensitivity/specificity were evaluated with 0.9596, 90.43%/100% in LUAD; 0.949, 86.95%/98.21% in LUSC TCGA training cohort; 0.94, 85.92%/97.37 in GEO 66

836; 0.91,89.17%/100% in GEO 83842 smokers; 0.948, 91.67%/100% in GEO83842 non-smokers independent testing cohort. Our study validates SCT, FOXD3, TRIM58 and TAC1 based gene panel has great potential in early recognition of NSCLC undetermined lung nodules. The findings can yield universally accurate

and robust markers facilitating early diagnosis and rapid severity examination.