{"id":149,"date":"2018-03-11T15:50:17","date_gmt":"2018-03-11T15:50:17","guid":{"rendered":"http:\/\/bme.ufl.edu\/labs\/rashidi\/?page_id=149"},"modified":"2025-11-18T13:58:17","modified_gmt":"2025-11-18T17:58:17","slug":"research","status":"publish","type":"page","link":"https:\/\/faculty.eng.ufl.edu\/rashidi\/research\/","title":{"rendered":"Research"},"content":{"rendered":"\n<p>Parisa Rashidi is the director of the \u201cIntelligent Health Lab\u201d (i-Heal). Her area of research includes developing machine learning and artificial intelligence methods for solving healthcare problems. More specifically, she is working on: (1) transforming patient care in the Intensive Care Unit by developing autonomous monitoring tools using advanced machine learning techniques, (2) developing intelligent tools for monitoring cognitive and mental conditions of community-dwelling patients. She has forged a highly collaborative research program across campus to address these problems, collaborating with several departments at the College of Medicine, including nephrology, anesthesiology, clinical neuropsychology, and aging. Her research is supported by the National Science Foundation (NSF), National Institute of Health (NIH), state grants, and internal grants.<\/p>\n\n\n\n<p><a href=\"https:\/\/scholar.google.com\/citations?user=Rtej0FIAAAAJ&amp;hl=en\">Google Scholar page<\/a><\/p>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h4 class=\"wp-block-heading\">Research Interests<\/h4>\n\n\n\n<p><\/p>\n\n\n\n<p><strong>Machine Learning<\/strong> |<strong> Natural Language Processing <\/strong>|<strong> Intelligent Health Systems <\/strong>|<strong> Biomedical Data Science<\/strong><\/p>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h4 class=\"wp-block-heading\">Research Projects<\/h4>\n\n\n\n<div class=\"wp-block-create-block-accordion-block\"><section class=\"accordion-section mb-5\"><div class=\"container-fluid\"><div class=\"row-fluid\"><div class=\"accordion closeAll\" id=\"parent6c88713b-31f9-4f6f-876a-ab6b3ceb1e2a\">\n<div class=\"wp-block-create-block-accordion-block-inner\"><div class=\"accordion-item\"><span class=\"accordion-header\" id=\"headingbb2f1fb6-bb71-408c-9e43-dd7e34b956f4\"><button class=\"accordion-button collapsed\" type=\"button\" data-bs-toggle=\"collapse\" data-bs-target=\"#collapsebb2f1fb6-bb71-408c-9e43-dd7e34b956f4\" aria-expanded=\"false\" aria-controls=\"bb2f1fb6-bb71-408c-9e43-dd7e34b956f4\">Intelligent ICU<\/button><\/span><div id=\"collapsebb2f1fb6-bb71-408c-9e43-dd7e34b956f4\" class=\"accordion-collapse collapse\" aria-labelledby=\"headingbb2f1fb6-bb71-408c-9e43-dd7e34b956f4\"><div class=\"accordion-body\"><div class=\"accordion-body-wrap\">\n<div class=\"wrap\">\n<div class=\"meta\">\n<p><strong>Pervasive sensing and Artificial Intelligence for Critical Care<\/strong><\/p>\n<\/div>\n<\/div>\n<div class=\"wrap\">\n<div class=\"image\">\n<div class=\"imageoverlay\">\n<p>Our\u00a0long-term goal\u00a0is to sense, quantify, and communicate patient condition in an autonomous, precise, and personalized manner. We\u00a0plan to build the foundation of an\u00a0intelligent ICU\u00a0by developing and validating pervasive context sensing, precise context inference, and situation-aware context communication using novel sensing and artificial intelligence technologies. This project is carried out at Intensive Care Units (ICU) at UF Health hospitals (UFH). Several sub-projects include:<\/p>\n<ol>\n<li>Patient Activity Recognition<\/li>\n<li>Facial Expression Analysis, including pain and anxiety<\/li>\n<li>Environment Characterization (noise, light, visitors)<\/li>\n<li>Delirium Characterization<\/li>\n<li>Using Gaming, virtual reality, and mixed reality in the ICU<\/li>\n<\/ol>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"accordion-btn-wrap\"><\/div><\/div><\/div><\/div><\/div>\n\n\n\n<div class=\"wp-block-create-block-accordion-block-inner\"><div class=\"accordion-item\"><span class=\"accordion-header\" id=\"heading2fa7a741-fc03-411c-ac1d-9386d28580ea\"><button class=\"accordion-button collapsed\" type=\"button\" data-bs-toggle=\"collapse\" data-bs-target=\"#collapse2fa7a741-fc03-411c-ac1d-9386d28580ea\" aria-expanded=\"false\" aria-controls=\"2fa7a741-fc03-411c-ac1d-9386d28580ea\">Trajectory Prediction in Hospitalized Patients<\/button><\/span><div id=\"collapse2fa7a741-fc03-411c-ac1d-9386d28580ea\" class=\"accordion-collapse collapse\" aria-labelledby=\"heading2fa7a741-fc03-411c-ac1d-9386d28580ea\"><div class=\"accordion-body\"><div class=\"accordion-body-wrap\">\n<div class=\"details\">\n<div class=\"wrap\">\n<div class=\"meta\">\n<p><strong>Predicting the status of patient throughout their hospital stay<\/strong><\/p>\n<\/div>\n<\/div>\n<div class=\"wrap\">\n<div class=\"image\">\n<div class=\"imageoverlay\"><span style=\"color: #313535; font-size: 1.25rem;\">We expect to facilitate early interventions by precisely predicting a patient\u2019s clinical trajectory using high-resolution data and using accurate deep learning models.<\/span><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"accordion-btn-wrap\"><\/div><\/div><\/div><\/div><\/div>\n\n\n\n<div class=\"wp-block-create-block-accordion-block-inner\"><div class=\"accordion-item\"><span class=\"accordion-header\" id=\"headingee9f2f18-d669-4fb2-9862-0094fd6d6525\"><button class=\"accordion-button collapsed\" type=\"button\" data-bs-toggle=\"collapse\" data-bs-target=\"#collapseee9f2f18-d669-4fb2-9862-0094fd6d6525\" aria-expanded=\"false\" aria-controls=\"ee9f2f18-d669-4fb2-9862-0094fd6d6525\">Mental Health &amp; AI<\/button><\/span><div id=\"collapseee9f2f18-d669-4fb2-9862-0094fd6d6525\" class=\"accordion-collapse collapse\" aria-labelledby=\"headingee9f2f18-d669-4fb2-9862-0094fd6d6525\"><div class=\"accordion-body\"><div class=\"accordion-body-wrap\">\n<div class=\"wrap\">\n<div class=\"meta\">\n<p><strong>Using Artificial Intelligence Techniques for Mental Health Therapy<\/strong><\/p>\n<\/div>\n<\/div>\n<div class=\"details\">\n<p>The goal of this project is to develop\u00a0 natural language processing and machine learning techniques to provide personalized treatments to customize and individualize online mental health treatment, the Intelligent Counseling System (ICS). More specifically, we focus on several problems:<\/p>\n<ol>\n<li>Therapy recommendation<\/li>\n<li>Language polarity detection<\/li>\n<li>Cognitive distortion detection<\/li>\n<\/ol>\n<\/div>\n<\/div><div class=\"accordion-btn-wrap\"><\/div><\/div><\/div><\/div><\/div>\n\n\n\n<div class=\"wp-block-create-block-accordion-block-inner\"><div class=\"accordion-item\"><span class=\"accordion-header\" id=\"heading7df48524-e438-4273-8ecb-5e8ee99cd597\"><button class=\"accordion-button collapsed\" type=\"button\" data-bs-toggle=\"collapse\" data-bs-target=\"#collapse7df48524-e438-4273-8ecb-5e8ee99cd597\" aria-expanded=\"false\" aria-controls=\"7df48524-e438-4273-8ecb-5e8ee99cd597\">Characterizing Postoperative Pain Signatures<\/button><\/span><div id=\"collapse7df48524-e438-4273-8ecb-5e8ee99cd597\" class=\"accordion-collapse collapse\" aria-labelledby=\"heading7df48524-e438-4273-8ecb-5e8ee99cd597\"><div class=\"accordion-body\"><div class=\"accordion-body-wrap\">\n<div class=\"wrap\">\n<div class=\"meta\">\n<p><strong>Finding Good Temporal Postoperative Pain Signatures<\/strong><\/p>\n<\/div>\n<\/div>\n<div class=\"wrap\">\n<div class=\"image\">\n<div class=\"imageoverlay\">\n<p>This project is a result of collaboration with Dr. Ptarick Tighe. It examines how postoperative pain scores change with respect to time using machine learning and advanced data science techniques such as shapelets and deep learning techniques.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"accordion-btn-wrap\"><\/div><\/div><\/div><\/div><\/div>\n\n\n\n<div class=\"wp-block-create-block-accordion-block-inner\"><div class=\"accordion-item\"><span class=\"accordion-header\" id=\"heading9bf2d678-99cb-4e0a-a8af-508da5fb7423\"><button class=\"accordion-button collapsed\" type=\"button\" data-bs-toggle=\"collapse\" data-bs-target=\"#collapse9bf2d678-99cb-4e0a-a8af-508da5fb7423\" aria-expanded=\"false\" aria-controls=\"9bf2d678-99cb-4e0a-a8af-508da5fb7423\">In-Community Health Monitoring<\/button><\/span><div id=\"collapse9bf2d678-99cb-4e0a-a8af-508da5fb7423\" class=\"accordion-collapse collapse\" aria-labelledby=\"heading9bf2d678-99cb-4e0a-a8af-508da5fb7423\"><div class=\"accordion-body\"><div class=\"accordion-body-wrap\">\n<div class=\"wrap\">\n<div class=\"meta\">\n<p><strong>Health monitoring using mHealth technology<\/strong><\/p>\n<\/div>\n<\/div>\n<p>Our long term goal is to develop an ecologically momentary assessment tool for capturing patient status in real time in the context of momentary physiologic and psychometric data. We have developed an ecologically momentary assessment framework using Samsung Gear S smartwatch to assess patient reported outcomes, as well as to automatically measure physiological and psychological parameters, especially in older adults. This project is carried out in collaboration with UF Institute on Aging.<\/p>\n<\/div><div class=\"accordion-btn-wrap\"><\/div><\/div><\/div><\/div><\/div>\n\n\n\n<div class=\"wp-block-create-block-accordion-block-inner\"><div class=\"accordion-item\"><span class=\"accordion-header\" id=\"headingc4a8b2a9-dd40-4eff-80ae-3cca184f9eab\"><button class=\"accordion-button collapsed\" type=\"button\" data-bs-toggle=\"collapse\" data-bs-target=\"#collapsec4a8b2a9-dd40-4eff-80ae-3cca184f9eab\" aria-expanded=\"false\" aria-controls=\"c4a8b2a9-dd40-4eff-80ae-3cca184f9eab\">Postoperative Risk Assessment<\/button><\/span><div id=\"collapsec4a8b2a9-dd40-4eff-80ae-3cca184f9eab\" class=\"accordion-collapse collapse\" aria-labelledby=\"headingc4a8b2a9-dd40-4eff-80ae-3cca184f9eab\"><div class=\"accordion-body\"><div class=\"accordion-body-wrap\">\n<div class=\"wrap\">\n<div class=\"meta\">\n<p><strong>Integrating data, algorithms and clinical reasoning for surgical risk assessment<\/strong><\/p>\n<\/div>\n<\/div>\n<div class=\"details\">\n<div class=\"details\">\n<p>This project is in collaboration with Dr. Azra Bihorac. It examines how surgical risk can be assessed using machine learning and advanced data analysis techniques.<\/p>\n<\/div>\n<\/div>\n<\/div><div class=\"accordion-btn-wrap\"><\/div><\/div><\/div><\/div><\/div>\n\n\n\n<div class=\"wp-block-create-block-accordion-block-inner\"><div class=\"accordion-item\"><span class=\"accordion-header\" id=\"heading66b80591-e808-42dd-a674-b675bb4a7fd9\"><button class=\"accordion-button collapsed\" type=\"button\" data-bs-toggle=\"collapse\" data-bs-target=\"#collapse66b80591-e808-42dd-a674-b675bb4a7fd9\" aria-expanded=\"false\" aria-controls=\"66b80591-e808-42dd-a674-b675bb4a7fd9\">Postoperative Cognitive Evaluation<\/button><\/span><div id=\"collapse66b80591-e808-42dd-a674-b675bb4a7fd9\" class=\"accordion-collapse collapse\" aria-labelledby=\"heading66b80591-e808-42dd-a674-b675bb4a7fd9\"><div class=\"accordion-body\"><div class=\"accordion-body-wrap\">\n<div class=\"wrap\">\n<div class=\"meta\">\n<p><strong>Presurgical Cognitive Evaluation via Digital clockfacE drawing<\/strong><\/p>\n<\/div>\n<\/div>\n<div class=\"details\">\n<div id=\"wrapper\">\n<div id=\"main\">\n<div class=\"fac-page currentpage\" data-url=\"https:\/\/bme.ufl.edu\/labs\/rashidi\/intelligent-health-systems-lab-i-heal\/research\/\" data-pos=\"p2\">\n<div id=\"inside\">\n<div class=\"vc_row wpb_row vc_row-fluid\">\n<div class=\"wpb_column vc_column_container vc_col-sm-12\">\n<div class=\"vc_column-inner\">\n<div class=\"wpb_wrapper\">\n<div class=\"details\">\n<p>This project is in collaboration with Dr. Patrick Tighe and Dr. catherine Price. It examines how deep learning and digital technology can be used to assess cognitive function in hospitalized patients.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div id=\"facwpfooter\">\n<div id=\"wpadminbar\" class=\"nojq\">\u00a0<\/div>\n<\/div>\n<\/div>\n<\/div><div class=\"accordion-btn-wrap\"><\/div><\/div><\/div><\/div><\/div>\n<\/div><\/div><\/div><\/section><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Parisa Rashidi is the director of the \u201cIntelligent Health Lab\u201d (i-Heal). Her area of research includes developing machine learning and artificial intelligence methods for solving healthcare problems. More specifically, she is working on: (1) transforming patient care in the Intensive Care Unit by developing autonomous monitoring tools using advanced machine learning techniques, (2) developing intelligent [&hellip;]<\/p>\n","protected":false},"author":468,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"page-templates\/page-sidebar-none.php","meta":{"_acf_changed":false,"inline_featured_image":false,"featured_post":"","footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-149","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/faculty.eng.ufl.edu\/rashidi\/wp-json\/wp\/v2\/pages\/149","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/faculty.eng.ufl.edu\/rashidi\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/faculty.eng.ufl.edu\/rashidi\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/faculty.eng.ufl.edu\/rashidi\/wp-json\/wp\/v2\/users\/468"}],"replies":[{"embeddable":true,"href":"https:\/\/faculty.eng.ufl.edu\/rashidi\/wp-json\/wp\/v2\/comments?post=149"}],"version-history":[{"count":4,"href":"https:\/\/faculty.eng.ufl.edu\/rashidi\/wp-json\/wp\/v2\/pages\/149\/revisions"}],"predecessor-version":[{"id":1769,"href":"https:\/\/faculty.eng.ufl.edu\/rashidi\/wp-json\/wp\/v2\/pages\/149\/revisions\/1769"}],"wp:attachment":[{"href":"https:\/\/faculty.eng.ufl.edu\/rashidi\/wp-json\/wp\/v2\/media?parent=149"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}