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In recent times, the concept of artificial intelligence (AI) in the healthcare system has increasingly gathered popularity. The medical fields and tech industry are continually interacting to improve technology. Tech companies, such as Microsoft, are investing more funding into AI healthcare innovations. In a bid to address healthcare challenges, Microsoft announced a five-year $40 million program in 2020. In 2021, AI sector funding increased by over 100%, with healthcare accounting for about one-fifth of overall funding.
Artificial intelligence simplifies the lives of doctors, hospital administrators, and even patients by performing tasks that are typically done by humans, but faster and cheaper. It helps health practitioners to improve operational efficiencies, streamline tasks, and simplify complex procedures.
Artificial intelligence has an inexhaustible list of benefits in healthcare, from identifying symptoms and making diagnoses to undertaking hospital administrative work such as making appointments and registering patients. It can assist in surgery and predict when an epidemic will break out. AI holds significant promise to transform and improve patient care and safety in the Emergency Room or ICU.
Recently, the University of Colorado School of Medicine, seeking to enhance clinical care through integrated computational technology, laboratory investigations, and artificial intelligence, announced the launch of its new department. The new Department of Biomedical Informatics (DBMI) will focus on addressing health disparities and improving healthcare quality using big data and AI.
The department is an offshoot of the University of Colorado (CU) School of Medicine’s Center for Health AI, which aims to make the University’s Anschutz Medical Campus a leader in translating data into advances in research practice, health care delivery, and population health and in using these to provide nationwide benefit through innovative technologies. Researchers at the DBMI, by leveraging AI and Colorado’s large population, hope to develop analytics solutions to serve people across the state.
Over the last few years, researchers at the CU have received notable recognitions. In 2021, they received a National Institutes of Health award to build clinical decision tools to improve patient outcomes and develop novel criteria to modernize pediatric sepsis diagnoses. Another remarkable project resulted in the development of a COVID-19 dashboard, which uses real-time electronic health record (EHR) data to predict decisions around the need for crisis care. The dashboard was later used by federal policymakers to make decisions about the pediatric COVID-19 response.
The DBMI’s leadership, building on trust and cooperation within the department, aims to close the gaps in biomedical innovation by focusing on equity within patient populations and professionals in the field. It is also collaborating with the CU Anschutz Office of Diversity, Equity, Inclusion (DEI) and Community Engagement and the CU School of Medicine DEI Committee in order to establish best practices and strategies for education and employment opportunities.
With a focus on promoting DEI in the field of biomedicine and biomedical informatics, the Department of Biomedical Informatics (DBMI) intends to significantly improve patient outcomes and decrease harmful biases in data collection and analysis that can lead to disparities.
Although artificial intelligence is undoubtedly changing the healthcare industry, the relatively new technology has also generated some concerns. The limitations identified include possible Inaccuracies and security risks, social bias, rendering people unemployed, and the need for human surveillance.
However, despite significant challenges, AI promises extraordinary benefits to the medical sector. This innovative technology has made possible the convenience and access to a wider range of healthcare for the rest of the world.
Artificial intelligence has been applied to predicting the flow of patients into the emergency department, monitoring patients in both the wards and the emergency department, and predicting the availability of beds in in-patients. Various forecasting methods that have been utilized in predicting patient flow include linear regression, time series regression, artificial neural networks, and exponential smoothing.
AI appears to be an ideal tool for optimising patient management in hospitals. Many AI algorithms are available for predicting and managing patient flow into the various departments of a hospital.
It is now estimated that the global digital health market will increase to around $640 billion by 2026. Through our expertise coupled with optimized networking, we will ensure that both investors and startups are on the ground floor of this health revolution. The event which is organized and curated alongside a team of doctors, attracts legislators and policymakers, medical professionals, and investors from across the world, addresses the opportunities and challenges driving this million-dollar forum.
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