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intelligence (AI), can assist in improving health and health care. Radiology images, e.g. X-rays, fundus image, dermascopic image, MRI, CT-scans and EHR, form the basic screening and diagnosis procedure for many
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will support and enhance a wide range of applications such as law enforcement, health, national security, marketing, and advertisement. Required knowledge Essential First class Honors or Masters degree
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Adversarial Machine Learning (AML) is a technique to fool a machine learning model through malicious input. Due to its significance in many scenarios, including security, privacy, and health
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Synthetic data generation has drawn growing attention due to the lack of training data in many application domains. It is useful for privacy-concerned applications, e.g. digital health applications
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make automated behavioural prediction a routine and simple process for all behavioural researchers. This would enhance the research into almost all mental health disorders. Greater understanding
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reasoning, where better and more transparent reasoning and decision making improve outcomes for end users, providing significant potential health, social and economic benefits. The PhD project will involve
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Antimicrobial resistance (AMR) is one of the most significant and immediate threats to health in Australia and globally. As an Infectious Diseases physician and researcher, the second supervisor is
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that is vital to their lives, such as information on their entitlements, public services, health, education or work opportunities. Timely access to information is essential to perform many economic, social
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and usage of the #SMART on #FHIR software paradigm Involves working with various real world health services and health IT partners #digitalhealth #health #EMR #hospital #software Learn more about
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to recruit a cohort of students with diverse background and skill sets in machine learning, cybersecurity, and digital health to work in the above directions in a collaborative manner. This project will