Events Calendar

11 Nov
ISP AI Forum: "Deep Learning Computational Vision to Advance Total Joint Arthroplasty (TJA) Research"
Event Type

Forums

Topic

Health & Wellness, Research, Technology

Target Audience

Undergraduate Students, Staff, Faculty, Graduate Students

University Unit
Intelligent Systems Program
Hashtag

#AI

Subscribe
Google Calendar iCal Outlook

ISP AI Forum: "Deep Learning Computational Vision to Advance Total Joint Arthroplasty (TJA) Research"

This is a past event.

Abstract: Orthopedic surgical procedures, and particularly total knee/hip arthroplasty (TKA/THA), are the most common and fastest growing surgeries in the United States. Almost 1.3 million TJA procedures occur on a yearly basis and more than 7 million Americans are currently living with artificial knee and/or hip joints. The widespread adoption of x-ray radiography and their availability at low cost, make them the principal method in assessing TJA and subtle TJA complications, such as osteolysis, implant loosening or infection over time, enabling surgeons to rule out complications and possible needs for revision surgeries. Rapid yet, with the growing number of TJA patients, the routine clinical and radiograph follow-up remain a daunting task for most orthopedic centers. It becomes an overwhelming amount of work, on a human scale, when we consider a radiologist or surgeon presented with the vast number of medical images daily. Smart computational strategies, such as artificial intelligence and deep learning computational vision are thus required to analyze arthroplasty radiographs automatically and objectively, enabling both naive and experienced practitioners to perform radiographic follow-up with greater ease and speed. In this talk, we will be discussing the effectiveness of modern computer vision strategies to advance TJA research. We, together, will explore what computational vision components do in TJA setting and how they impact the TJA research agenda.
 

Bio: Ahmad P. Tafti, PhD is an Assistant Professor of Health Informatics in the School of Health and Rehabilitation Sciences at the University of Pittsburgh, where he is also leading the Pitt HexAI Research Laboratory. Starting from July 2022, he serves the community as the Vice Chair of IEEE Computer Society at Pittsburgh. Ahmad P. Tafti has a deep passion for AI-Powered healthcare informatics and health data science with better patient diagnosis, prognosis, and treatment using large-scale multiple clinical data sources and advanced computational algorithms, including artificial intelligence and deep learning computational methods. He earned his PhD in Computer Science from the University of Wisconsin-Milwaukee and since then, he has been on a quest to explore and solve problems that are worth it and make the most positive impact on people’s lives. Ahmad P. Tafti has been successfully leveraging his background in descriptive and predictive machine learning modeling, image and clinical text analysis, and big data analytics to find solutions to a diverse range of problems in healthcare informatics. He is indeed passionate about diverse biomedical data sources along with artificial intelligence methods and their applications in healthcare. Ahmad P. Tafti is the 2021 SiiM Imaging Informatics Innovator awardee, Mayo Clinic Benefactor funded CDAs Orthopedics Career Development awardee, Mayo Clinic Transform the Practice awardee, an NVIDIA GPU awardee, and GE Healthcare Honorable Mention awardee. To date, he has authored 45+ peer-reviewed publications, organizing numerous workshops on intelligent health systems and he has served on the program committee of 15+ conferences, symposiums, and journals in AI and health data science.

RSVP for Zoom information: https://pitt.co1.qualtrics.com/jfe/form/SV_6ta133EtL9Ndk0u

Friday, November 11 at 12:30 p.m. to 1:30 p.m.

Virtual Event

ISP AI Forum: "Deep Learning Computational Vision to Advance Total Joint Arthroplasty (TJA) Research"

Abstract: Orthopedic surgical procedures, and particularly total knee/hip arthroplasty (TKA/THA), are the most common and fastest growing surgeries in the United States. Almost 1.3 million TJA procedures occur on a yearly basis and more than 7 million Americans are currently living with artificial knee and/or hip joints. The widespread adoption of x-ray radiography and their availability at low cost, make them the principal method in assessing TJA and subtle TJA complications, such as osteolysis, implant loosening or infection over time, enabling surgeons to rule out complications and possible needs for revision surgeries. Rapid yet, with the growing number of TJA patients, the routine clinical and radiograph follow-up remain a daunting task for most orthopedic centers. It becomes an overwhelming amount of work, on a human scale, when we consider a radiologist or surgeon presented with the vast number of medical images daily. Smart computational strategies, such as artificial intelligence and deep learning computational vision are thus required to analyze arthroplasty radiographs automatically and objectively, enabling both naive and experienced practitioners to perform radiographic follow-up with greater ease and speed. In this talk, we will be discussing the effectiveness of modern computer vision strategies to advance TJA research. We, together, will explore what computational vision components do in TJA setting and how they impact the TJA research agenda.
 

Bio: Ahmad P. Tafti, PhD is an Assistant Professor of Health Informatics in the School of Health and Rehabilitation Sciences at the University of Pittsburgh, where he is also leading the Pitt HexAI Research Laboratory. Starting from July 2022, he serves the community as the Vice Chair of IEEE Computer Society at Pittsburgh. Ahmad P. Tafti has a deep passion for AI-Powered healthcare informatics and health data science with better patient diagnosis, prognosis, and treatment using large-scale multiple clinical data sources and advanced computational algorithms, including artificial intelligence and deep learning computational methods. He earned his PhD in Computer Science from the University of Wisconsin-Milwaukee and since then, he has been on a quest to explore and solve problems that are worth it and make the most positive impact on people’s lives. Ahmad P. Tafti has been successfully leveraging his background in descriptive and predictive machine learning modeling, image and clinical text analysis, and big data analytics to find solutions to a diverse range of problems in healthcare informatics. He is indeed passionate about diverse biomedical data sources along with artificial intelligence methods and their applications in healthcare. Ahmad P. Tafti is the 2021 SiiM Imaging Informatics Innovator awardee, Mayo Clinic Benefactor funded CDAs Orthopedics Career Development awardee, Mayo Clinic Transform the Practice awardee, an NVIDIA GPU awardee, and GE Healthcare Honorable Mention awardee. To date, he has authored 45+ peer-reviewed publications, organizing numerous workshops on intelligent health systems and he has served on the program committee of 15+ conferences, symposiums, and journals in AI and health data science.

RSVP for Zoom information: https://pitt.co1.qualtrics.com/jfe/form/SV_6ta133EtL9Ndk0u

Friday, November 11 at 12:30 p.m. to 1:30 p.m.

Virtual Event

Event Type

Forums

University Unit
Intelligent Systems Program
Hashtag

#AI

Powered by the Localist Community Events Calendar ©