Representing Human Anatomy for Computation and Communication: Synergistic Development of an Anatomical Ontology and Semantically-Augmented Anatomical Graphics

代表人体解剖学进行计算和通信：解剖本体论和语义增强解剖图形的协同发展

• 批准号: 10635511
• 负责人: Melissa Clarkson
• 金额: $ 38.25万
• 依托单位: UNIVERSITY OF KENTUCKY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-25 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10635511
• 关键词: Address; Affect; Anatomic Models; Anatomy; Biomedical Research; Clinical; Clinical Medicine; Communication; Communities; Computer software; Computers; Data Science; Data Set; Development; Disease; Education; Human; Human Resources; Informatics; Information Resources; Information Systems; Intelligence; Knowledge; Libraries; Medical Illustration; Medicine; Modeling; Modernization; Names; Ontology; Patient Care; Patients; Pattern; Persons; Positioning Attribute; Production; Readability; Recording of previous events; Research; Research Personnel; Resources; Scheme; Semantics; Source; Standardization; Structure; Text; Time; Variant; Visual; Work; biomedical ontology; body system; clinical application; computational anatomy; computational reasoning; data integration; data modeling; design; human model; knowledge base; knowledgebase; medical information system; multidisciplinary; next generation; ontology development; preservation; skills; trustworthiness; web app

Project summary Ontologies represent a domain of knowledge in a form that can be used by both computers and people. Biomedical ontologies provide standardized representations of knowledge that underlie modern biomedical research and serve as knowledge bases for enabling intelligent software applications. The Foundational Model of Anatomy (FMA) is an ontology of human anatomy and has a rich history as one of the first biomedical ontologies. After 20 years of development, two issues that affect the ability of the FMA to continue to serve as a source for standardized, computable knowledge of human anatomy have become apparent: First, variation in modeling schemes and inter-author variation have introduced inconsistencies, such that similar structures within the body are represented in slightly different ways. Second, ontologies rely on textual and logical representations, yet visual representations are often more effective for communicating about anatomy. These issues highlight the need for a next-generation resource for human anatomy that is optimized for use by both computers and people. In this project, we will undertake synergistic development of an ontology of human anatomy and standardized visual representations of human anatomy. Aim 1: To develop an ontology of human anatomy suitable for computational reasoning that will serve as a knowledgebase for the next generation of medical information systems, we will create the Foundational Model of Human Anatomy (FMHA) as a derivative of the FMA. Aim 2: To provide standardized visual representations of human anatomy for use in information systems, we will develop libraries of composable graphics depicting canonical anatomy that will be augmented with computer-readable semantics. Aim 3: To demonstrate use of the FMHA and standardized graphics to address real-world needs in research, education, and clinical contexts, we will expand our graphic libraries beyond depictions of canonical anatomy and develop two web applications. Aim 4: To demonstrate how developers can leverage the FMHA and graphics in their own web applications, we will develop a web application for graphically-driven exploration of the Disease Ontology. By developing the FMHA and anatomical graphics libraries as highly-curated resources, they will serve as trustworthy knowledge sources for biomedical applications in data science. By integrating text- based and visual representations of anatomy, we will help to ensure that researchers accurately annotate the anatomical content of datasets and models using FMHA classes, thereby helping to preserve the integrity of integrated datasets and models. 1

Project summary Ontologies represent a domain of knowledge in a form that can be used by both computers and people. Biomedical ontologies provide standardized representations of knowledge that underlie modern biomedical research and serve as knowledge bases for enabling intelligent software applications. The Foundational Model of Anatomy (FMA) is an ontology of human anatomy and has a rich history as one of the first biomedical ontologies. After 20 years of development, two issues that affect the ability of the FMA to continue to serve as a source for standardized, computable knowledge of human anatomy have become apparent: First, variation in modeling schemes and inter-author variation have introduced inconsistencies, such that similar structures within the body are represented in slightly different ways. Second, ontologies rely on textual and logical representations, yet visual representations are often more effective for communicating about anatomy. These issues highlight the need for a next-generation resource for human anatomy that is optimized for use by both computers and people. In this project, we will undertake synergistic development of an ontology of human anatomy and standardized visual representations of human anatomy. Aim 1: To develop an ontology of human anatomy suitable for computational reasoning that will serve as a knowledgebase for the next generation of medical information systems, we will create the Foundational Model of Human Anatomy (FMHA) as a derivative of the FMA. Aim 2: To provide standardized visual representations of human anatomy for use in information systems, we will develop libraries of composable graphics depicting canonical anatomy that will be augmented with computer-readable semantics. Aim 3: To demonstrate use of the FMHA and standardized graphics to address real-world needs in research, education, and clinical contexts, we will expand our graphic libraries beyond depictions of canonical anatomy and develop two web applications. Aim 4: To demonstrate how developers can leverage the FMHA and graphics in their own web applications, we will develop a web application for graphically-driven exploration of the Disease Ontology. By developing the FMHA and anatomical graphics libraries as highly-curated resources, they will serve as trustworthy knowledge sources for biomedical applications in data science. By integrating text- based and visual representations of anatomy, we will help to ensure that researchers accurately annotate the anatomical content of datasets and models using FMHA classes, thereby helping to preserve the integrity of integrated datasets and models. 1