Critically-ill children 'need more aftercare'

BBC News

When he was just six months old, Sam went into intensive care for several months after a severe infection left him unable to breathe properly. The stress of that experience still affects Sam and his family now. As evidence emerges of the long-term impact of critical illness, do survivors need more specialist psychology support? "Sam is a remarkably happy and sociable child, but does react to sudden loud noises by getting very distressed and holding his breath," says Jo Reynolds, his mother. "He also gets very upset when he has to go through medical procedures," she adds.


Artificial intelligence-based algorithm for intensive care of traumatic brain injury

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A recent Finnish study published in Scientific Reports presents the first artificial intelligence (AI)-based algorithm designed for use in intensive care units for treating patients with severe traumatic brain injury. The project is a collaborative project between three Finnish university hospitals: Helsinki University Hospital, Kuopio University Hospital and Turku University Hospital. Traumatic brain injury (TBI) is a significant global cause of mortality and morbidity with an increasing incidence, especially in low-and-middle income countries. The most severe TBIs are treated in intensive care units (ICU), but in spite of the proper and high-quality care, about one in three patients dies. Patients that suffer from severe TBI are unconscious, which makes it challenging to accurately monitor the condition of the patient during intensive care.


Artificial intelligence-based algorithm for intensive care of traumatic brain injury

#artificialintelligence

A recent Finnish study published in Scientific Reports presents the first artificial intelligence (AI)-based algorithm designed for use in intensive care units for treating patients with severe traumatic brain injury. The project is a collaborative project between three Finnish university hospitals: Helsinki University Hospital, Kuopio University Hospital and Turku University Hospital. Traumatic brain injury (TBI) is a significant global cause of mortality and morbidity with an increasing incidence, especially in low-and-middle income countries. The most severe TBIs are treated in intensive care units (ICU), but in spite of the proper and high-quality care, about one in three patients dies. Patients that suffer from severe TBI are unconscious, which makes it challenging to accurately monitor the condition of the patient during intensive care.


Artificial intelligence-based algorithm for intensive care of traumatic brain injury

#artificialintelligence

Traumatic brain injury (TBI) is a significant global cause of mortality and morbidity with an increasing incidence, especially in low-and-middle income countries. The most severe TBIs are treated in intensive care units (ICU), but in spite of the proper and high-quality care, about one in three patients dies. Patients that suffer from severe TBI are unconscious, which makes it challenging to accurately monitor the condition of the patient during intensive care. In the ICU, many tens of variables are continuously monitored (e.g. However, only one variable, such as intracranial pressure, may yield hundreds of thousands of data points per day.


High-performance computing aids traumatic brain injury research - Verdict Medical Devices

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The project began in March of this year but is still in its initial stages. A new multi-year project involving several American universities and national laboratories aims to use supercomputing resources and artificial intelligence (AI) to enable a precision medicine approach for treating traumatic brain injury (TBI). The participating institutions include the Department of Energy's (DOE) Lawrence Livermore (LLNL), Lawrence Berkeley (LBNL) and Argonne (ANL) national laboratories, in collaboration with the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) consortium led by the University of California, San Francisco (UCSF) and involving other leading universities across the US. Funded primarily by the National Institutes of Health's National Institute of Neurological Disorders and Stroke (NINDS) DOE scientists will analyse some of the largest and most complex TBI patient data sets collected, including advanced computed tomography (CT) and magnetic resonance imaging (MRI), proteomic and genomic biomarkers and clinical outcomes. To do this they will use artificial intelligence based technologies and supercomputing resources.