Medicine and Health Sciences Commons^™

Revolutionizing Revenue Cycle Management: Ai's Impact On Healthcare Organizations, Rachel Pennington, Alberto Coustasse

Management Faculty Research

Revenue Cycle Management (RCM) stands as a cornerstone in healthcare, overseeing the intricate processes involved in capturing, managing, and collecting revenue generated from patient services. However, the landscape of RCM has long been plagued by inefficiencies. These inefficiencies underscore the urgency for innovative approaches, and the integration of AI emerges as a promising solution to streamline processes and optimize revenue capture.

Navigating Through Chaos, Hoong Chuin Lau

Asian Management Insights

How AI and optimisation models can strengthen supply chain resilience.

Eyris: From The Lab To The Market, Steven Miller, David Gomulya, Mahima Rao-Kachroo

Asian Management Insights

Singapore’s trailblazer AI algorithm for detecting diabetes-related eye diseases. Can you imagine getting the results of your eye disease screening within minutes rather than days? This capability is what EyRIS, a Singapore-based start-up that uses the AI (Artificial Intelligence)-driven Singapore Eye LEsion Analyzer (SELENA+) algorithm to screen for diabetes-related eye diseases, set out to productise and commercialise.

Scope And Limitations Of Chatgpt In Research And Academic Writing, Shyam Pyare Singh, Imran Ahmed Khan, Shaila Kumari Mitra

Digital Journal of Clinical Medicine

Background: ChatGPT has proven to be an invaluable tool, enabling human-like interactions, and facilitating knowledge exchange. It possesses the ability to generate coherent and contextually relevant responses based on the input it receives. In essence, ChatGPT responds to anything in a conversational manner and provides an output that looks like human writing. However, with the rapid advancement of medical research, there is an increasing concern that ChatGPT may be abused to create articles devoid of clinical reasoning and critical thinking.

METHODS: A through literature search was conducted on PubMed and Google scholar to find relevant article according to objective.

RESULTS: …

Regulation Of Health Ai Chatbots In Ontario, Mingi Chu

Electronic Thesis and Dissertation Repository

Artificial Intelligence (AI) has made remarkable strides in healthcare, from revolutionizing medical imaging, patient support, research insight, and health education. However, a recent shift from query-based to interactive and regenerative AI presents a question of properly facilitating its development. Upon close inspection, regulations and policy adaptations lag behind the rapidly advancing field of medical AI which raises concerns over governance and societal implications. This paper explains some of the technical and ethical considerations surrounding the use of health AI applications with chatbots as a specific example. It evaluates the existing policies and regulations in Ontario, Canada, that govern the production …

Docai, Riley Badnin, Justin Brunings

Computer Science and Software Engineering

DocAI presents a user-friendly platform for recording, transcribing, summarizing, and classifying doctor-patient consultations. The application utilizes AssemblyAI for conversational transcription, and the user interface allows users to either live-record consultations or upload an existing MP3 file. The classification process, powered by 'ml-classify-text,' organizes the consultation transcription into SOAP (Subjective, Objective, Assessment, and Plan) format – a widely used method of documentation for healthcare providers. The result of this development is a simple yet effective interface that effectively plays the role of a medical scribe. However, the application is still facing challenges of inconsistent summarization from the AssemblyAI backend. Future work …

Artificial Intelligence In The Medical Field: Medical Review Sentiment Analysis, Nicholas Podlesak

Honors Capstones

In this research project, natural language processing techniques’ ability to accurately classify medical text was measured to reinforce the relevance of artificial intelligence in the medical field. Sentiment analyses (analyses to determine whether the text was positive or negative) were performed on the prescription drug reviews in an open-source dataset using four different models: lexical, a neural network, a support vector machine, and a logistic regression model. Each model’s effectiveness was gauged by its ability to correctly classify unlabeled drug reviews (i.e., a percentage representing accuracy). The machine learning models were able to accurately classify the text, while the lexical …

A New Era: Utilizing Technology Tools To Enhance Elder Independence, April Lisa Phelps

Doctoral Dissertations and Projects

The goal of this integrative review was to examine the multitude of technology tools and the evidence which supports their use to enhance elders’ independence when residing at home. Multiple journal articles and books published between July 2015 and July 2020 were examined using the PRISMA model for evidence to support or oppose the use of technology to enhance the elders’s independence. A total of 27 articles were included in the final review. An exploration of gaps in knowledge related to the issue of elders using technology tools such as wearable sensors, artificial intelligence, home monitoring, robots, mHealth, Internet of …

Artificial Intelligence And The Challenge For Rural Medicine, James Denvir

Marshall Journal of Medicine

Recent advances in artificial intelligence, machine learning, and deep learning are beginning to have an impact on everyday experiences, from natural language processing used in automated telephone call centers to semi-autonomous vehicles. These techniques have also been applied to medical care. In this editorial we discuss applications of AI to medicine and argue for a proactive approach to include rural medicine in this paradigm shift.