Machine learning is a potentially effective method for predicting the response to platinum-based treatment for ovarian cancer. However, the predictive performance of various machine learning methods and variables is still a matter of controversy and debate.

The onset of mental health problems peaks between adolescence and young adulthood; however, young people face barriers to treatment and are often reluctant to seek professional help. Many are instead seeking support and information regarding their mental health via the Web, especially via social networking sites (SNSs), and hence, there is a promising opportunity to use SNSs to deliver or integrate with youth-focused online mental health interventions. Previous reviews have evaluated the effectiveness of SNSs for specific disorders in young people; however, none of the reviews have covered the breadth of SNS-based youth mental health interventions available across all mental health issues.

Despite the increase in use and high expectations of digital health solutions, scientific evidence about the effectiveness of electronic health (eHealth) and other aspects such as usability and accuracy is lagging behind. eHealth solutions are complex interventions, which require a wide array of evaluation approaches that are capable of answering the many different questions that arise during the consecutive study phases of eHealth development and implementation. However, evaluators seem to struggle in choosing suitable evaluation approaches in relation to a specific study phase.

Self-management support is one mechanism by which telehealth interventions have been proposed to facilitate management of long-term conditions.

Patient education is a crucial element within health care. It is a known predictor for increased engagement in shared decision making, improved medication and treatment adherence, higher levels of satisfaction, and even better treatment outcomes. Unfortunately, often patients only remember a very limited amount of medical information. An important reason is that most patients are simply not capable of processing large amounts of new medical information in a short time. Apps for smartphones and tablets have the potential to actively educate patients by providing them with timely information through the use of push notifications.

The prioritization of sustainable patient-centered care in contemporary health care has resulted in an increased focus on patient empowerment, which in turn is considered to facilitate patient independence, self-management, and self-efficacy. However, a definitional consensus of empowerment remains elusive, impeding efforts to translate the conceptual ideals of empowerment into a measurable entity associated with changes in health care behavior or outcomes. The rapid integration of technology in health care serves to add another layer of complexity in the measurability and operationalization of empowerment and helps to create a specific context in which this conceptual entity should be further examined.

Bipolar disorder (BD) is the 10th most common cause of frailty in young individuals and has triggered morbidity and mortality worldwide. Patients with BD have a life expectancy 9 to 17 years lower than that of normal people. BD is a predominant mental disorder, but it can be misdiagnosed as depressive disorder, which leads to difficulties in treating affected patients. Approximately 60% of patients with BD are treated for depression. However, machine learning provides advanced skills and techniques for better diagnosis of BD.

Globally, diabetes affects approximately 500 million people and is predicted to affect up to 700 million people by 2045. In Australia, the ongoing impact of colonization produces inequity in health care delivery and inequality in health care outcomes for First Nations Peoples, with diabetes rates 4 times those of non-Indigenous Australians. Evidence-based clinical practice has been shown to reduce complications of diabetes-related foot disease, including ulceration and amputation, by 50%. However, factors such as a lack of access to culturally safe care, geographical remoteness, and high costs associated with in-person care are key barriers for First Nations Peoples in accessing evidence-based care, leading to the development of innovative mobile health (mHealth) apps as a way to increase access to health services and improve knowledge and self-care management for people with diabetes.

Drug-induced suicide has been debated as a crucial issue in both clinical and public health research. Published research articles contain valuable data on the drugs associated with suicidal adverse events. An automated process that extracts such information and rapidly detects drugs related to suicide risk is essential but has not been well established. Moreover, few data sets are available for training and validating classification models on drug-induced suicide.

The influence of social media among adolescent peer groups can be a powerful change agent.

ChatGPT is a 175-billion-parameter natural language processing model that is already involved in scientific content and publications. Its influence ranges from providing quick access to information on medical topics, assisting in generating medical and scientific articles and papers, performing medical data analyses, and even interpreting complex data sets.

Engaging patients in the delivery of health care has the potential to improve health outcomes and patient satisfaction. Patient portals may enhance patient engagement by enabling patients to access their electronic medical records (EMRs) and facilitating secure patient-provider communication.

Immersive virtual reality (IVR) applications are gaining popularity in health care education. They provide an uninterrupted, scaled environment capable of simulating the full magnitude of sensory stimuli present in busy health care settings and increase students' competence and confidence by providing them with accessible and repeatable learning opportunities in a fail-safe environment.

The use of electronic cigarettes (e-cigarettes), also known as vaping, has risen exponentially among North American youth in recent years and has become a critical public health concern. The marketing strategies used by e-cigarette companies have been associated with the uptick in use among youth, with video advertisements on television and other electronic platforms being the most pervasive strategy. It is unknown how these advertisements may be tapping into youth needs and preferences.

When investigating voice disorders a series of processes are used when including voice screening and diagnosis. Both methods have limited standardized tests, which are affected by the clinician's experience and subjective judgment. Machine learning (ML) algorithms have been used as an objective tool in screening or diagnosing voice disorders. However, the effectiveness of ML algorithms in assessing and diagnosing voice disorders has not received sufficient scholarly attention.

The accurate assessment and acquisition of facial anatomical information significantly contributes to enhancing the reliability of treatments in dental and medical fields, and has applications in fields such as craniomaxillofacial surgery, orthodontics, prosthodontics, orthopedics, and forensic medicine. Mobile device-compatible 3D facial scanners have been reported to be an effective tool for clinical use, but the accuracy of digital facial impressions obtained with the scanners has not been explored.

Social media is increasingly used to deliver HIV interventions for key populations worldwide. However, little is known about the specific uses and effects of social media on human immunodeficiency virus (HIV) interventions.

Digital health solutions can provide populations with musculoskeletal pain with high-reach, low-cost, easily accessible, and scalable patient education and self-management interventions that meet the time and resource restrictions.

Accessibility is acknowledged as a key to inclusion in the Convention of Rights for People with Disabilities. An inaccessible design can result in exclusion from eHealth and cause disability among people who have impairments.

HIV continues to disproportionately affect men who have sex with men (MSM) and transgender women (TW). Undiagnosed HIV is a major driver of HIV transmission rates, and increasing the uptake of regular HIV testing and facilitating timely initiation of HIV treatment is a global HIV prevention priority. However, MSM and TW experience a range of barriers that limit their access to testing and other prevention services. Given their growing ubiquity, digital communication technologies are increasingly being used to support HIV prevention efforts, and a growing number of studies have trialed the use of digital technology to promote HIV testing among MSM and TW.