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        <description>Artificial Intelligence and Machine Learning in Healthcare Mini-Elective 2021-22

Introduction

Artificial intelligence (AI) is the scientific discipline that develops computer algorithms and machines that apply the algorithms to perform tasks that require human intelligence. The origins of AI can be traced to Alan Turing who proposed the question “Can machines think?” and argued that machines can indeed think intelligently. While it is arguable if machines can think, it is undoubtedly clear tod…</description>
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        <description>Clinical Informatics

Clinical informatics is the application of computing methods including artificial intelligence in the delivery healthcare services. Predictive and causal models using big data and artificial intelligence will be increasingly used in clinical decision-making. These models will power a new generation of clinical decision support tools in the coming decade. The</description>
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        <description>Learning Electronic Medical Record (LEMR) System



This work is funded by a R01 grant from NLM, NIH.

As electronic medical records (EMRs) capture increasing amounts of data per patient, compiling a clinical narrative becomes cognitively more demanding. This information overload is particularly challenging in settings such as the intensive care unit (ICU) where a new data point may be added to a patient’s record almost every minute. Moreover, the display of patient data in current EMRs is not s…</description>
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Principal Investigator

	*  Shyam Visweswaran, MD, PhD

Students

	*  Amin Tajgardoon, MS, (Pursuing PhD in Intelligent Systems Program)
	*  Joshua W Anderson, (Pursuing PhD in Intelligent Systems Program)
	*  Nihal Murali, (Pursuing PhD in Intelligent Systems Program)

Alumni

	*</description>
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        <description>Misc

Statistics

	*  All About that Bayes: Probability, Statistics, and the Quest to Quantify Uncertainty - Kristin Lennox
	*  Everything wrong with statistics (and how to fix it) - Kristin Lennox

Deep learning

	*  Practical Deep Learning for Coders
	*  Dive into Deep Learning
	*  Deep Learning textbook -- Ian Goodfellow, Yoshua Bengio and Aaron Courville
	*  Mathematics for Machine Learning 
	*  11-785 Introduction to Deep Learning -- CMU Fall 2020

Python

	*  Jupyter Notebook: An Introduct…</description>
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See Google Scholar for recent papers.

107. A novel personalized random forest algorithm for clinical outcome prediction. 

Johnson A, Cooper GF, Visweswaran S. 

Virtual MedInfo Symposium. October 2021. 

([paper])

106. The National COVID Cohort Collaborative (N3C) Rationale, design, infrastructure, and deployment</description>
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        <description>Research

The Vis Lab is focused on on the application of artificial intelligence and machine learning to problems in biomedicine with a specific focus on developing intelligent electronic medical record systems, precision medicine and personalized modeling, data mining and causal discovery from biomedical data, and research data warehousing.</description>
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        <description>Teaching

BIOINF 2119 Probabilistic Methods in Artificial Intelligence (Onsite course)

Taught every spring, 2010 - 2017

This course introduces fundamental concepts and methods in artificial intelligence that are applicable to problems in biomedicine. This course is designed for students who do not necessarily have a background in computer science. The course provides the foundations in artificial intelligence methods including search (breadth-first search, depth-first search, greedy search, et…</description>
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        <title>start</title>
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        <description>Shyam Visweswaran, MD, PhD (PI of the Vis Lab)



I am Interim Chair and UPMC Endowed Chair of Biomedical Informatics with training in artificial intelligence (AI), biomedical informatics, and clinical neurology. I lead interdisciplinary research advancing AI in biomedicine, with a focus on AI-enabled clinical decision support, ethically grounded clinical algorithms, patient-specific modeling, causal discovery from complex biomedical data, and ontology development.</description>
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