Contemporary Applications of Machine Learning for Device Therapy in Heart Failure.

Despite a better understanding of the underlying pathogenesis of heart failure (HF), pharmacotherapy, surgical, and percutaneous interventions do not prevent disease progression in all patients, and a significant proportion of patients end up requiring advanced therapies. Machine learning (ML) is gaining wider acceptance in cardiovascular medicine because of its ability to incorporate large, complex, and multidimensional data and to potentially facilitate the creation of predictive models not constrained by many of the limitations of traditional statistical approaches. With the coexistence of "big data" and novel advanced analytic techniques using ML, there is ever-increasing research into applying ML in the context of HF with the goal of improving patient outcomes. Through this review, the authors describe the basics of ML and summarize the existing published reports regarding contemporary applications of ML in device therapy for HF while highlighting the limitations to widespread implementation and its future promises.

Experiences with basic body awareness therapy as an add-on to cognitive behavioural therapy among Danish military veterans with PTSD: An interview study.

BACKGROUND: The Danish Veterans Centre offers a body-orientated therapy, Basic Body Awareness Therapy (BBAT), in addition to the psychological trauma-focused therapy to military veterans suffering from symptoms of post-traumatic stress disorder (PTSD). This study explored how the veterans a) experienced BBAT as a physiotherapeutic approach and as an add-on treatment to their usual Cognitive Behavioural Therapy (CBT) and b) whether it makes sense for the individual veteran to incorporate BBAT into their treatment. MATERIALS AND METHODS: Individual semi-structured interviews with four veterans who had completed 12 BBAT sessions concurrently with their usual CBT treatment. Interviews were transcribed and analysed using Malterud's version of Giorgi's 4-step systematic text condensation. RESULTS: Three main categories emerged: "Effects of treatment", "The setting of the treatment" and "Complementary nature of BBAT and CBT". Within each category were 2-5 underlying subgroups. Participants found it made sense to combine BBAT with their CBT since it benefitted them differently and addressed their bodily symptoms and improved body perception/awareness. CONCLUSION: BBAT showed potential as a supplement to CBT and seemed to benefit the veterans through focusing on bodily symptoms and how to calm them. Future studies are needed because of the limited research on the topic.