AI and machine learning, deep learning in particular, have made significant progress recently, revolutionizing the medical computing practice. In the past decades, I have been collaborating closely with medical experts in the NYC region, such as Mt. Sinai Hospital, Memorial Sloan-Kettering Institute, Columbia Univ. medical school, Yale Univ. Medical School, and Johns Hopkins Univ., on a broad array of AI-enabled medical computing projects. In this talk, I will introduce my recent work on the use of AI in cancer treatment and remote simultaneous medical interpretations. First, a broad array of different medical modalities has to be effectively employed to effect better medical data analysis, whereof enabling computer graphics, signal processing, and computer vision techniques must be called in. We developed a unified GUI-based system to put multimodal medical together for better cancer treatment planning purposes. In a second project, by using robust curve fitting and space/time local and global analysis, we devised an effective human lung respiratory movement tracking algorithm with outstanding performance, so that the radiation therapy can be more effective. Next, a mixture of experts, each of which is a CNN-based UNet algorithm, is introduced to effectively single out the cancer region. Our ongoing smart and cheap non-invasive bio-sign sensing devices and algorithms are next introduced to ensure more precise and non-invasive sensing can be achieved for more patients. Finally, the Large Language Models (LLMs) are exploited to achieve remote simultaneous medical interpretation, riding on the immense power of recent progress in LLMs. From these concrete projects, it can be seen that mathematical/statistical modeling, data structure and algorithm pipeline development, creative use of multimodal computing, and various AI/ML algorithms can be incorporated to achieve improved healthcare. Effective use of AI/ML, including current LLM and various foundation models, has a bright future in medical computing. Co-sponsored by: Fairleigh Dickinson University Speaker(s): Jie Wei, Agenda: IEEE North Jersey Section Computer Chapter and Signal Processing Chapter Seminar Title: AI in Medical Computing: Cancer Treatment and Remote Simultaneous Medical Interpretations Speaker: Prof. Jie Wei, Department of Computer Science, CCNY Time: 12:30pm-1:30pm Fairleigh Dickinson University 1000 River Road, Building: Becton Hall, Room Number: 205 Teaneck, New Jersey, United States 07666 For additional information about the venue and parking, please contact Dr. Hong Zhao zhao@fdu.edu Bldg: Becton Hall 205, 1000 River Road, Teaneck, New Jersey, United States, 07666