Artificial Intelligence in Radiotherapy Treatment Planning: Present and Future.

Treatment planning is an essential step of the radiotherapy workflow. It has become more sophisticated over the past couple of decades with the help of computer science, enabling planners to design highly complex radiotherapy plans to minimize the normal tissue damage while persevering sufficient tumor control. As a result, treatment planning has become more labor intensive, requiring hours or even days of planner effort to optimize an individual patient case in a trial-and-error fashion. More recently, artificial intelligence has been utilized to automate and improve various aspects of medical science. For radiotherapy treatment planning, many algorithms have been developed to better support planners. These algorithms focus on automating the planning process and/or optimizing dosimetric trade-offs, and they have already made great impact on improving treatment planning efficiency and plan quality consistency. In this review, the smart planning tools in current clinical use are summarized in 3 main categories: automated rule implementation and reasoning, modeling of prior knowledge in clinical practice, and multicriteria optimization. Novel artificial intelligence-based treatment planning applications, such as deep learning-based algorithms and emerging research directions, are also reviewed. Finally, the challenges of artificial intelligence-based treatment planning are discussed for future works

Assessment of the feasibility of an ultra-low power, wireless digital patch for the continuous ambulatory monitoring of vital signs.

BACKGROUND AND OBJECTIVES: Vital signs are usually recorded at 4–8 h intervals in hospital patients, and deterioration between measurements can have serious consequences. The primary study objective was to assess agreement between a new ultra-low power, wireless and wearable surveillance system for continuous ambulatory monitoring of vital signs and a widely used clinical vital signs monitor. The secondary objective was to examine the system's ability to automatically identify and reject invalid physiological data. SETTING: Single hospital centre. PARTICIPANTS: Heart and respiratory rate were recorded over 2 h in 20 patients undergoing elective surgery and a second group of 41 patients with comorbid conditions, in the general ward. OUTCOME MEASURES: Primary outcome measures were limits of agreement and bias. The secondary outcome measure was proportion of data rejected. RESULTS: The digital patch provided reliable heart rate values in the majority of patients (about 80%) with normal sinus rhythm, and in the presence of abnormal ECG recordings (excluding aperiodic arrhythmias such as atrial fibrillation). The mean difference between systems was less than ±1 bpm in all patient groups studied. Although respiratory data were more frequently rejected as invalid because of the high sensitivity of impedance pneumography to motion artefacts, valid rates were reported for 50% of recordings with a mean difference of less than ±1 brpm compared with the bedside monitor. Correlation between systems was statistically significant (p<0.0001) for heart and respiratory rate, apart from respiratory rate in patients with atrial fibrillation (p=0.02). CONCLUSIONS: Overall agreement between digital patch and clinical monitor was satisfactory, as was the efficacy of the system for automatic rejection of invalid data. Wireless monitoring technologies, such as the one tested, may offer clinical value when implemented as part of wider hospital systems that integrate and support existing clinical protocols and workflows

Use of nonintrusive sensor-based information and communication technology for real-world evidence for clinical trials in dementia

Cognitive function is an important end point of treatments in dementia clinical trials. Measuring cognitive function by standardized tests, however, is biased toward highly constrained environments (such as hospitals) in selected samples. Patient-powered real-world evidence using information and communication technology devices, including environmental and wearable sensors, may help to overcome these limitations. This position paper describes current and novel information and communication technology devices and algorithms to monitor behavior and function in people with prodromal and manifest stages of dementia continuously, and discusses clinical, technological, ethical, regulatory, and user-centered requirements for collecting real-world evidence in future randomized controlled trials. Challenges of data safety, quality, and privacy and regulatory requirements need to be addressed by future smart sensor technologies. When these requirements are satisfied, these technologies will provide access to truly user relevant outcomes and broader cohorts of participants than currently sampled in clinical trials

Complexity stage model of the medical device development based on economic evaluation-MedDee

The development of a new product is essential for the progress and success of any company. The medical device market is very specific, which is challenging. Therefore, this paper assesses an economic model for medical device evaluation using the economic, health, technology regulatory, and present market knowledge to enable the cost-time conception for any applicant. The purpose of this study is to propose a comprehensive stage model of the medical device development to subsequently describe the financial expenditure of the entire development process. The identification of critical steps was based on the literature review, and analysis, and a comparison of the available medical device development stages and directives. Furthermore, a preliminary assessment of the medical device development steps and procedures on the basis of the interviews was performed. Six interviews were conducted with an average duration of one hour, focusing on areas: relevance and level of detail of the medical device development stages, involvement of economic methods, and applicability of the proposed model. Subsequently, the improvement and modification of the medical device investment process, based on respondents' responses, were conducted. The authors have proposed the complexity model MedDee-Medical Devices Development by Economic Evaluation. This model is comprised of six phases: initiation, concept, design, production, final verification, and market disposition in which the economic methods are incorporated.Web of Science125art. no. 175

The Men's Safer Sex (MenSS) trial: protocol for a pilot randomised controlled trial of an interactive digital intervention to increase condom use in men

Sexually transmitted infections (STI) are a major public health problem. Condoms provide effective protection but there are many barriers to use. Face-to-face health promotion interventions are resource-intensive and show mixed results. Interactive digital interventions may provide a suitable alternative, allowing private access to personally tailored behaviour change support. We have developed an interactive digital intervention (the Men's Safer Sex (MenSS) website) which aims to increase condom use in men. We describe the protocol for a pilot trial to assess the feasibility of a full-scale randomised controlled trial of the MenSS website in addition to usual sexual health clinical care