What You Should Know:
– Certis Oncology Solutions, a translational science and emerging technology leader in preclinical oncology research, is pleased to announce the commercial launch of CertisOI Assistant™, an innovative chatbot tool designed to enhance…
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Estimating progression of acute ischemic brain lesions – or biological lesion age – holds huge practical importance for hyperacute stroke management. The current best method for determining lesion age from non-contrast computerised tomography (NCCT),…
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Parkinson’s disease (PD) increases fall risk, leading to injuries and reduced quality of life. Accurate fall risk assessment is crucial for effective care planning. Traditional assessments are subjective and time-consuming, while recent assessment methods…
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Aaron Timm, EVP and Chief Commercial Officer at Vivalink
The concept of Hospital-at-Home (HaH), first introduced in the 1990s and not widely used, gained renewed attention and increased deployment across the United States during the…
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This scoping review evaluates recent advancements in data-driven technologies for predicting non-neonatal pediatric sepsis, including artificial intelligence, machine learning, and other methodologies. Of the 27 included studies, 23 (85%) were single-center investigations, and 16…
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By expediting the first step of spatial omics data analysis, the new artificial intelligence model provides detailed insights into how a disease develops and progresses at the cellular level and can advance precise diagnostics and…
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The current assessment of Parkinson’s disease (PD) relies on dynamic motor tasks, limiting accessibility. This study aimed to propose an innovative approach to identifying PD and its stages using static standing balance and machine…
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People with a history of injecting drug use are a priority for eliminating blood-borne viruses and sexually transmissible infections. Identifying them for disease surveillance in electronic medical records (EMRs) is challenged by sparsity of…
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Researchers from South Korea have built machine learning-based models that can predict mood episodes using only sleep and circadian rhythm data from wearable devices. The team comprised researchers from the Institute for Basic Sciences (IBS),…
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Background: The increasing prevalence of sedentary lifestyles has prompted the development of innovative public health interventions, such as smartphone applications that deliver personalised exercise programs. The widespread availability of mobile technologies (e.g., smartphone apps…
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