Evaluation And Improvement Of The Implementation Of The Intention To Treat Model In Controlled Trials Of Psychotherapies
Funder
National Health and Medical Research Council
Funding Amount
$409,000.00
Summary
Randomized controlled trials (RCTs) are the best way to determine whether patients benefit from a new treatment. In these trials patients are randomly assigned to the new, active treatment, or to a placebo or existing treatment. The groups are compared at the end of the trial. RCTs may be mounted for psychotherapy and educational programs as well as for new drugs and other medical procedures. A major problem for RCTs concerns their statistical analysis when some participants drop out before the ....Randomized controlled trials (RCTs) are the best way to determine whether patients benefit from a new treatment. In these trials patients are randomly assigned to the new, active treatment, or to a placebo or existing treatment. The groups are compared at the end of the trial. RCTs may be mounted for psychotherapy and educational programs as well as for new drugs and other medical procedures. A major problem for RCTs concerns their statistical analysis when some participants drop out before the end of the trial. Dropout is common in trials. Participants may drop out because they feel no benefit from the treatment, dislike side effects, or even because they have recovered quickly. Thus, to compare the groups remaining at the end of trial may introduce serious bias. The Intention to Treat (ITT) principle which has been widely adopted states that outcomes from all patients who enter a trial should be compared at its end. To achieve this, the last available observation for a participant who withdraws is often 'carried forward' to the end of the trial. While currently believed to be conservative, there is evidence that this approach is not always optimal. This project will examine the way in which dropout is treated in trials of two common psychiatric conditions: depression and anxiety disorders. The project will also undertake simulation research to investigate which of a number of modern methods of data analysis yield the most accurate results when participants drop out, and how changes in the design of trials might improve accuracy. The project is important because it will enable researchers to improve the conduct of trials in the future. Erroneous conclusions drawn from RCTs stand to condemn those suffering from disorders to ineffective treatment and to lead to the premature abandonment of potentially useful interventions which are falsely claimed to lack efficacy.Read moreRead less
Effective software vulnerability detection for web services. This project aims to design and implement new and better methods to find vulnerabilities in software services delivered over the web or through the cloud, as well as methods for proving the absence of certain types of vulnerability. So-called injection attacks are pervasive and generally considered the most important security threat on today's Internet. The programming languages used for software services tend to use strings as a unive ....Effective software vulnerability detection for web services. This project aims to design and implement new and better methods to find vulnerabilities in software services delivered over the web or through the cloud, as well as methods for proving the absence of certain types of vulnerability. So-called injection attacks are pervasive and generally considered the most important security threat on today's Internet. The programming languages used for software services tend to use strings as a universal data structure, which unfortunately makes it hard to separate trusted code from untrusted user-provided data. This project intends to develop novel program analysis tools and string constraint solvers, and employ these tools to support sophisticated automated reasoning about string manipulating software.Read moreRead less
Human interaction with context-aware computing systems. Context-aware systems can provide seamless support of IT applications in a variety of technologies and therefore can improve: (i) work performance and adoption of IT in many industries; and (ii) the quality of life through better support for health services, education, and everyday tasks. Currently proposed solutions for context-aware systems fail to deliver systems which are usable for non-IT professionals. The proposed project will show h ....Human interaction with context-aware computing systems. Context-aware systems can provide seamless support of IT applications in a variety of technologies and therefore can improve: (i) work performance and adoption of IT in many industries; and (ii) the quality of life through better support for health services, education, and everyday tasks. Currently proposed solutions for context-aware systems fail to deliver systems which are usable for non-IT professionals. The proposed project will show how to design context-aware systems that are usable and whose autonomic decisions can be trusted. Additional benefits include increased scientific competitiveness of Australia, strengthened collaboration with international research institutions, and high quality graduates (PhDs, Masters, Honours).Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0347131
Funder
Australian Research Council
Funding Amount
$115,490.00
Summary
Intelligent Computer System to Access Information Directly from the Brain Using High Resolution Electroencephalography and Repetitive Transcranial Magnetic Stimulation. The ambitious aim of this project is to create a novel intelligent computer system which accesss information from the brain. To do this we use repetitive Transcranial Magnetic Stimulation and high resolution Electroencephalography.
3D Diffusion Models for Generating and Understanding 3D Scenes. Diffusion models, such as DALL-E2 and Imagen, have achieved remarkable success in generating photorealistic images and hold promise to solve long-standing computer vision problems. However, 3D scene generation remains unexplored. This research project aims to bridge the gap by developing 3D diffusion models capable of generating complete 3D scenes. This will advance our theoretical understanding of diffusion in complex 3D environmen ....3D Diffusion Models for Generating and Understanding 3D Scenes. Diffusion models, such as DALL-E2 and Imagen, have achieved remarkable success in generating photorealistic images and hold promise to solve long-standing computer vision problems. However, 3D scene generation remains unexplored. This research project aims to bridge the gap by developing 3D diffusion models capable of generating complete 3D scenes. This will advance our theoretical understanding of diffusion in complex 3D environments and open up new possibilities for applications in fields such as virtual reality, architecture, and city planning. The proposed 3D diffusion models will also enhance the accuracy of computer vision tasks related to 3D scene understanding, such as object detection, tracking, and semantic segmentation.Read moreRead less
MemberGuard: Protecting Machine Learning Privacy from Membership Inference. Machine Learning has become a core part of many real-world applications. However, machine learning models are vulnerable to membership inference attacks. In these attacks, an adversary can infer if a given data record has been part of the model's training data. In this project, the team aims to develop new techniques that can be used to counter these attacks, such as 1) new analytical models for membership leakage, 2) ne ....MemberGuard: Protecting Machine Learning Privacy from Membership Inference. Machine Learning has become a core part of many real-world applications. However, machine learning models are vulnerable to membership inference attacks. In these attacks, an adversary can infer if a given data record has been part of the model's training data. In this project, the team aims to develop new techniques that can be used to counter these attacks, such as 1) new analytical models for membership leakage, 2) new methods for susceptibility diagnosis, 3) new defences that leverage privacy and utility. Data-oriented services are estimated to be valuable assets in the future. These techniques can help Australia gain cutting edge advantage in machine learning security and privacy and protect its intellectual property on these services.Read moreRead less
Scalable & Accountable Privacy-Preserving Blockchain with Enhanced Security. This project aims to address the scalability and accountability of privacy-preserving blockchain by advancing cryptographic techniques. This project expects to develop scalable protocols for privacy-preserving blockchain while also adding accountability for authority to trace cyber crime activities, which is a missing piece in any state-of-the-art public blockchain system. Expected outcomes of this project include not o ....Scalable & Accountable Privacy-Preserving Blockchain with Enhanced Security. This project aims to address the scalability and accountability of privacy-preserving blockchain by advancing cryptographic techniques. This project expects to develop scalable protocols for privacy-preserving blockchain while also adding accountability for authority to trace cyber crime activities, which is a missing piece in any state-of-the-art public blockchain system. Expected outcomes of this project include not only practical solutions for protecting sensitive data recorded in blockchain but also crucial techniques to make the blockchain accountable for practical applications with enhanced security. This project provides significant benefits, such as building a trusted environment for sensitive transactions in the digital economy.Read moreRead less