Tag: Digital medicine
Validation and application of computer vision algorithms for video-based tremor analysis
Tremor is one of the most common neurological symptoms. Its clinical and neurobiological complexity necessitates novel approaches for granular phenotyping. Instrumented neurophysiological analyses have proven useful, but are highly resource-intensive and lack broad accessibility….
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PatchSorter: a high throughput deep learning digital pathology tool for object labeling
The discovery of patterns associated with diagnosis, prognosis, and therapy response in digital pathology images often requires intractable labeling of large quantities of histological objects. Here we release an open-source labeling tool, PatchSorter, which…
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Development of an effective predictive screening tool for prostate cancer using the ClarityDX machine learning platform
The current prostate cancer (PCa) screen test, prostate-specific antigen (PSA), has a high sensitivity for PCa but low specificity for high-risk, clinically significant PCa (csPCa), resulting in overdiagnosis and overtreatment of non-csPCa. Early identification…
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Development and validation of a smartphone-based deep-learning-enabled system to detect middle-ear conditions in otoscopic images
Middle-ear conditions are common causes of primary care visits, hearing impairment, and inappropriate antibiotic use. Deep learning (DL) may assist clinicians in interpreting otoscopic images. This study included patients over 5 years old from…
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Five million nights: temporal dynamics in human sleep phenotypes
Sleep monitoring has become widespread with the rise of affordable wearable devices. However, converting sleep data into actionable change remains challenging as diverse factors can cause combinations of sleep parameters to differ both between…
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From wearable sensor data to digital biomarker development: ten lessons learned and a framework proposal
Wearable sensor technologies are becoming increasingly relevant in health research, particularly in the context of chronic disease management. They generate real-time health data that can be translated into digital biomarkers, which can provide insights…
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Head movement dynamics in dystonia: a multi-centre retrospective study using visual perceptive deep learning
Dystonia is a neurological movement disorder characterised by abnormal involuntary movements and postures, particularly affecting the head and neck. However, current clinical assessment methods for dystonia rely on simplified rating scales which lack the…
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Digital health technologies need regulation and reimbursement that enable flexible interactions and groupings
Digital Health Technologies (DHTs) are being applied in a widening range of scenarios in medicine. We describe the emerging phenomenon of the grouping of individual DHTs, with a clinical use case and regulatory approval…
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Effectiveness of telehealth versus in-person care during the COVID-19 pandemic: a systematic review
In this systematic review, we compared the effectiveness of telehealth with in-person care during the pandemic using PubMed, CINAHL, PsycINFO, and the Cochrane Central Register of Controlled Trials from March 2020 to April 2023….
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