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International Conference on Electrical engineering and informatics, ICEEI

作者： Arlinta Christy Barus Dian Ira Putri Hutasoit Joel Hunter Siringoringo Yusfi Apriyanti Siahaan Informatics Engineering Study Program Del Institute of Technology J1. Tobasa Sumatera Utara Indonesia Informatics Engineering Study Program Del Institute of Technology Jl. Sisingamangaraja Kec. Laguboti Kab. Tobasa Sumatera Utara Indonesia

Nowadays, software testing is viewed as an important phase in software engineering life cycle as it aims to improve the quality of software under development. Due to limited software testing tools available for free, many developers cannot do a comprehensive testing to the software under development before launching the software. For this reason, this research aims to provide a prototype of a software testing tool that can be used as an initial base model for further development. The tool implements white box testing method that means the testing explores source codes of software under test to find the errors inside. We focus on one of data flow coverage techniques known as all p-uses coverage. The tool is able to calculate the all p-uses coverage percentage of the software under testing.

关键词： Software Software testing Prototypes informatics Electrical engineering Software engineering

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GIS modeling using fuzzy logic approach in mineral prospecting based on geophysical data

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AIP Conference Proceedings 2016年第1期1711卷

作者： Harman Setyadi Lilik Eko Widodo Sudarto Notosiswoyo Putri Saptawati Arief Ismanto Iip Hardjana 1Doctorate Student Mine Engineering Study Program – Faculty of Mine and Petroleum Engineering Institute Technology Bandung Jl. Ganesa 10 Bandung 40132 - INDONESIA 2Earth Resources Exploration Group - Faculty of Mine and Petroleum Engineering Institute Technology Bandung Jl. Ganesa 10 Bandung 40132 – INDONESIA 3Informatics– STIE Institute Technology Bandung Jl. Ganesa 10 Bandung 40132 - INDONESIA 4J. Resources Nusantara Equity Tower 48th floor SCBD. Jl. Jendral Sudirman Kav 52-53 Jakarta 12190 - INDONESIA

The geophysical exploration method is the superior over the project area due to the dense of vegetation and thick soil so very limited geological outcrops. Contrast of physical properties of every different rock type should be able to be distinguished by the geophysical data. Fuzzy logic approach and weight of evidence were used for geophysical data modeling. Posterior probability was used to calculate the weight of evidence (WofE) of every fuzzy map memberships. By combining each rock type model, the model provides better result compared from the model from mixed rock type on the data training. This method is able to eliminate the potential interference of different geophysical signature. So that, the understanding the geological feature of the area is key success for the mineral prosperity modeling. We verified the model by site visiting and drilling and it is estimated about 90% confident.

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

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BMC NEUROSCIENCE 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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FANTOM5 CAGE profiles of human and mouse samples

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Scientific Data 2017年第1期4卷 1-10页

作者： Noguchi, Shuhei Arakawa, Takahiro Fukuda, Shiro Furuno, Masaaki Hasegawa, Akira Hori, Fumi Ishikawa-Kato, Sachi Kaida, Kaoru Kaiho, Ai Kanamori-Katayama, Mutsumi Kawashima, Tsugumi Kojima, Miki Kubosaki, Atsutaka Manabe, Ri-Ichiroh Murata, Mitsuyoshi Nagao-Sato, Sayaka Nakazato, Kenichi Ninomiya, Noriko Nishiyori-Sueki, Hiromi Noma, Shohei Saijyo, Eri Saka, Akiko Sakai, Mizuho Simon, Christophe Suzuki, Naoko Tagami, Michihira Watanabe, Shoko Yoshida, Shigehiro Arner, Peter Axton, Richard A. Babina, Magda Kenneth Baillie, J. Barnett, Timothy C. Beckhouse, Anthony G. Blumenthal, Antje Bodega, Beatrice Bonetti, Alessandro Briggs, James Brombacher, Frank Carlisle, Ailsa J. Clevers, Hans C. Davis, Carrie A. Detmar, Michael Dohi, Taeko Edge, B. Albert S. Edinger, Matthias Ehrlund, Anna Ekwall, Karl Endoh, Mitsuhiro Enomoto, Hideki Eslami, Afsaneh Fagiolini, Michela Fairbairn, Lynsey Farach-Carson, Mary C. Faulkner, Geoffrey J. Ferrai, Carmelo Fisher, Malcolm E. Forrester, Lesley M. Fujita, Rie Furusawa, Jun-Ichi Geijtenbeek, Teunis B. Gingeras, Thomas Goldowitz, Daniel Guhl, Sven Guler, Reto Gustincich, Stefano Ha, Thomas J. Hamaguchi, Masahide Hara, Mitsuko Hasegawa, Yuki Herlyn, Meenhard Heutink, Peter Hitchens, Kelly J. Hume, David A. Ikawa, Tomokatsu Ishizu, Yuri Kai, Chieko Kawamoto, Hiroshi Kawamura, Yuki I. Kempfle, Judith S. Kenna, Tony J. Kere, Juha Khachigian, Levon M. Kitamura, Toshio Klein, Sarah Peter Klinken, S. Knox, Alan J. Kojima, Soichi Koseki, Haruhiko Koyasu, Shigeo Lee, Weonju Lennartsson, Andreas MacKay-Sim, Alan Mejhert, Niklas Mizuno, Yosuke Morikawa, Hiromasa Morimoto, Mitsuru Moro, Kazuyo Morris, Kelly J. Motohashi, Hozumi Mummery, Christine L. Nakachi, Yutaka Nakahara, Fumio Nakamura, Toshiyuki Nakamura, Yukio Nozaki, Tadasuke Ogishima, Soichi Ohkura, Naganari Ohno, Hiroshi Ohshima, Mitsuhiro Okada-Hatakeyama, Mariko Okazaki, Yasushi Orlando, Valerio Ovchinnikov, Dmitry A. Passier, Robert Patrikakis, Margaret Pombo, Ana Pradhan-Bhatt, Swati Qin, Xian-Yang Rehli, Michael Rizzu, Patrizia Roy, S Division of Genomic Technologies RIKEN Center for Life Science Technologies Yokohama Kanagawa 230-0045 Japan RIKEN Omics Science Center Yokohama Kanagawa 230-0045 Japan Department of Medicine Karolinska Institutet Stockholm 14186 Sweden Karolinska University Hospital Center for Metabolism and Endocrinology Stockholm 14186 Sweden Scottish Centre for Regenerative Medicine University of Edinburgh 5 Little France Drive Edinburgh EH164UU United Kingdom Department of Dermatology and Allergy Charite University Medicine Berlin Charitéplatz 1 Berlin 10117 Germany Roslin Institute and Royal School of Veterinary Studies University of Edinburgh Edinburgh EH259RG United Kingdom Australian Infectious Diseases Research Centre University of Queensland St Lucia 4072 QLD Australia School of Chemistry and Molecular Biosciences University of Queensland St Lucia 4072 QLD Australia Bio-Rad Laboratories Pty Ltd Hercules 94547 CA United States University of Queensland Diamantina Institute University of Queensland Woolloongabba 4102 QLD Australia IRCCS Fondazione Santa Lucia Via del Fosso di Fiorano 64 Rome 00143 Italy Australian Institute for Bioengineering and Nanotechnology University of Queensland Brisbane St Lucia 4072 QLD Australia Division of Immunology Institute of Infectious Diseases and Molecular Medicine University of Cape Town Anzio Road Observatory 7925 South Africa Immunology of Infectious Diseases Faculty of Health Sciences South African Medical Research Council University of Cape Town Anzio Road 7925 South Africa International Centre for Genetic Engineering and Biotechnology Cape Town Component Anzio Road 7925 South Africa Hubrecht Institute Royal Netherlands Academy of Arts and Sciences Uppsalalaan 8 3584 Netherlands University Medical Centre Utrecht Postbus 85500 Utrecht 3508 Netherlands Genomics Cold Spring Harbor Laboratory Cold Spring Harbor New York 11797 NY United States Institute of Pharmaceutical Sciences ETH Zurich Vladi

In the FANTOM5 project, transcription initiation events across the human and mouse genomes were mapped at a single base-pair resolution and their frequencies were monitored by CAGE (Cap Analysis of Gene Expression) coupled with single-molecule sequencing. Approximately three thousands of samples, consisting of a variety of primary cells, tissues, cell lines, and time series samples during cell activation and development, were subjected to a uniform pipeline of CAGE data production. The analysis pipeline started by measuring RNA extracts to assess their quality, and continued to CAGE library production by using a robotic or a manual workflow, single molecule sequencing, and computational processing to generate frequencies of transcription initiation. Resulting data represents the consequence of transcriptional regulation in each analyzed state of mammalian cells. Non-overlapping peaks over the CAGE profiles, approximately 200,000 and 150,000 peaks for the human and mouse genomes, were identified and annotated to provide precise location of known promoters as well as novel ones, and to quantify their activities.

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Proceedings from the 9th annual conference on the science of dissemination and implementation: Washington, DC, USA. 14-15 December 2016

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Implement Sci 2017年第SUPPL 1期12卷 48-48页

作者： David Chambers Lisa Simpson Gila Neta Ulrica von Thiele Schwarz Antoinette Percy-Laurry Gregory A. Aarons Ross Brownson Amanda Vogel Shannon Wiltsey Stirman Kenneth Sherr Rachel Sturke Wynne E. Norton Allyson Varley Cynthia Vinson Lisa Klesges Suzanne Heurtin-Roberts M. Rashad Massoud Leighann Kimble Arne Beck Claire Neely Jennifer Boggs Carmel Nichols Wen Wan Erin Staab Neda Laiteerapong Nathalie Moise Ravi Shah Susan Essock Margaret Handley Amy Jones Jay Carruthers Karina Davidson Lauren Peccoralo Lloyd Sederer Todd Molfenter Ashley Scudder Sarah Taber-Thomas Kristen Schaffner Amy Herschell Eva Woodward Jeffery Pitcock Mona Ritchie JoAnn Kirchner Julia E. Moore Sobia Khan Shusmita Rashid Jamie Park Melissa Courvoisier Sharon Straus Daniel Blonigen Allison Rodriguez Luisa Manfredi Andrea Nevedal Joel Rosenthal David Smelson Christine Timko Nicole Stadnick Jennifer Regan Miya Barnett Anna Lau Lauren Brookman-Frazee Erick Guerrero Karissa Fenwick Yinfei Kong Gregory Aarons Rebecca Lengnick-Hall Benjamin Henwood Nina Sayer Craig Rosen Robert Orazem Brandy Smith Lindsey Zimmerman David Lounsbury Rachel Kimerling Jodie A. Trafton Steven Lindley Rahul Bhargava Hal Roberts Laura Gibson Gabriel J. Escobar Vincent Liu Benjamin Turk Arona Ragins Patricia Kipnis Ashley Ketterer Gruszkowski Michael W. Kennedy Emily Rentschler Drobek Lior Turgeman Aleksandra Sasha Milicevic Terrence L. Hubert Larissa Myaskovsky Youxu C. Tjader Robert J. Monte Kathryn G. Sapnas Edmond Ramly Diane R Lauver Christie M Bartels Shereef Elnahal Andrea Ippolito Hillary Peabody Carolyn Clancy Randall Cebul Thomas Love Douglas Einstadter Shari Bolen Brook Watts Vera Yakovchenko Angela Park William Lukesh Donald R. Miller David Thornton Mari-Lynn Drainoni Allen L. Gifford Shawna Smith Julia Kyle Mark S Bauer Daniel Eisenberg Celeste Liebrecht Michelle Barbaresso Amy Kilbourne Elyse Park Giselle Perez Jamie Ostroff Sarah Greene Michael Parchman Brian Austin Eric Larson Stefanie Ferreri Chris Shea Megan Smith Kea Turner Jennifer Bacci Kyle Bigham Geoffr Division of Cancer Control and Population Sciences National Cancer Institute Rockville MD 20850 USA AcademyHealth Washington DC 20009 USA Department of Learning Informatics Management and Ethics Karolinska Institutet Stockholm 17177 Sweden Department of Psychiatry University of California San Diego San Diego CA 92093 USA George Warren Brown School of Social Work Washington University in St. Louis St. Louis MO 63130 USA Center for Global Health National Cancer Institute Rockville MD 20850 USA Dissemination and Training Division VA National Center for PTSD Palo Alto CA 94305 USA Department of Global Health University of Washington Seattle WA 98105 USA Center for Global Health Studies Fogarty International Center National Institutes of Health Bethesda MD 20912 USA School of Public Health University of Alabama at Birmingham Birmingham AL 35243 USA School of Public Health University of Memphis Memphis TN 38152 USA USAID Applying Science to Strengthen and Improve Systems (ASSIST) Project Bethesda Maryland 20814 USA Institute for Health Research Kaiser Permanente Denver CO 80231 USA ICSI Institute for Clinical Systems Improvement Bloomington MN 55425 USA Medicine University of Chicago Chicago IL 60637 USA Medicine Columbia University Medical Center New York NY 10032 USA Psychiatry Columbia University New York NY 10032 USA General Internal Medicine Epidemiology and Biostatistics University of California San Francisco San Francisco CA 94110 USA New York State Office of Mental Health New York NY 10001 USA Medicine Icahn School of Medicine at Mount Sinai New York NY 10029 USA Center for Health Enhancement System Studies University of Wisconsin Madison WI 53706 USA Department of Psychiatry University of Pittsburgh Pittsburgh PA 15213 USA Psychology University at Buffalo Buffalo NY 14260 USA Department of Psychology West Virginia University Morgantown WV 26506 USA MIRECC VA North Little Rock AR 72114 USA QUERI for Team-Based Behavioral Health Centr

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Compressed sensing for thoracic MRI with partial random circulant matrices

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Telkomnika 2012年第1期10卷 147-154页

作者： Swastika, Windra Haneishi, Hideaki Informatics Engineering Study Program Ma Chung University Villa Puncak Tidar N/01 Malang Indonesia Research Center for Frontier Medical Engineering Chiba University 1-33 Yayoi-cho Inage-ku Chiba 263-8522 Japan

The use of circulant matrix as the sensing matrix in compressed sensing (CS) scheme has recently been proposed to overcome the limitation of random or partial Fourier matrices. Aside from reducing computational complexity, the use of circulant matrix for magnetic resonance (MR) image offers the feasibility in hardware implementations. This paper presents the simulation of compressed sensing for thoracic MR imaging with circulant matrix as the sensing matrix. The comparisons of reconstruction of three different type MR images using circulant matrix are investigated in term of number of samples, number of iteration and signal to noise ratio (SNR). The simulation results showed that circulant matrix works efficiently for encoding the MR image of respiratory organ, especially for smooth and sparse image in spatial domain. © 2012 Universitas Ahmad Dahlan.

关键词： Magnetic resonance

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Collaboration model of software development

Collaboration model of software development

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International Conference on Electrical engineering and informatics, ICEEI

作者： Tien Fabrianti Kusumasari Iping Supriana Kridanto Surendro Husni Sastramihardja Information System Program Study STMIK 1M Bandung Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Indonesia

Software development is a series of processes activity involving more than one person, especially in medium to large software projects. Each activity of software development is carried out by various combination of different individual. Collaboration occurs in every phase of the process software development. The right team collaboration method is one of the important things in success software development. This research is focused to develop collaboration model of software development to meet time schedule, budget, scope, and software quality. The collaboration model of software development is generated from survey of collaboration method (about face to face and virtual collaboration) and software development methodology especially agile methodology. The direct collaboration was used in the software specification processes, and combination (with a direct and virtual) collaboration was used during software design, implementation, and validation. Team coordination in every process of software development was done with face to face method. The same artifacts were used in this collaboration model with some collaboration software tools. Combination between face to face and virtual communication was used in this model. The model is implemented in small case software development project. During the software development, some measurement is carried out. The measurement included the measurement of project completion time, cost, software specification, and software quality. The software is developed in time schedule (two months), cost under budged, and meet specification. In addition, the software has built a fairly good quality. Thus, this collaboration model good use in software development to achieved accuracy of schedule, cost, scope, and quality.

关键词： Collaboration programming Face Software measurement Software tools Software quality

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Graph Artificial Intelligence in Medicine

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Biomedical Data Science 1000年第1期7卷 345-368页

作者： Ruth Johnson Michelle M. Li Ayush Noori Owen Queen Marinka Zitnik 1Department of Biomedical Informatics Harvard Medical School Boston Massachusetts USA email: marinka@hms.harvard.edu 2Berkowitz Family Living Laboratory Harvard Medical School Boston Massachusetts USA 3Bioinformatics and Integrative Genomics Program Harvard Medical School Boston Massachusetts USA 4Department of Computer Science Harvard John A. Paulson School of Engineering and Applied Sciences Allston Massachusetts USA 5Broad Institute of MIT and Harvard Cambridge Massachusetts USA 7Kempner Institute for the Study of Natural and Artificial Intelligence Harvard University Allston Massachusetts USA 6Harvard Data Science Initiative Cambridge Massachusetts USA

In clinical artificial intelligence (AI), graph representation learning, mainly through graph neural networks and graph transformer architectures, stands out for its capability to capture intricate relationships and structures within clinical datasets. With diverse data—from patient records to imaging—graph AI models process data holistically by viewing modalities and entities within them as nodes interconnected by their relationships. Graph AI facilitates model transfer across clinical tasks, enabling models to generalize across patient populations without additional parameters and with minimal to no retraining. However, the importance of human-centered design and model interpretability in clinical decision-making cannot be overstated. Since graph AI models capture information through localized neural transformations defined on relational datasets, they offer both an opportunity and a challenge in elucidating model rationale. Knowledge graphs can enhance interpretability by aligning model-driven insights with medical knowledge. Emerging graph AI models integrate diverse data modalities through pretraining, facilitate interactive feedback loops, and foster human–AI collaboration, paving the way toward clinically meaningful predictions.

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