首页|University of Massachusetts Chan Medical School Reports Findings in Machine Lear ning (Future of neurocritical care: Integrating neurophysics, multimodal monitor ing, and machine learning)
University of Massachusetts Chan Medical School Reports Findings in Machine Lear ning (Future of neurocritical care: Integrating neurophysics, multimodal monitor ing, and machine learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on Machine Learning is the subject o f a report. According to news reporting from Worcester, Massachusetts, by NewsRx editors, the research stated, "Multimodal monitoring (MMM) in the intensive car e unit (ICU) has become increasingly sophisticated with the integration of neuro physical principles. However, the challenge remains to select and interpret the most appropriate combination of neuromonitoring modalities to optimize patient o utcomes." The news correspondents obtained a quote from the research from the University o f Massachusetts Chan Medical School, "This manuscript reviewed current neuromoni toring tools, focusing on intracranial pressure, cerebral electrical activity, m etabolism, and invasive and noninvasive autoregulation monitoring. In addition, the integration of advanced machine learning and data science tools within the I CU were discussed. Invasive monitoring includes analysis of intracranial pressur e waveforms, jugular venous oximetry, monitoring of brain tissue oxygenation, th ermal diffusion flowmetry, electrocorticography, depth electroencephalography, a nd cerebral microdialysis. Noninvasive measures include transcranial Doppler, ty mpanic membrane displacement, near-infrared spectroscopy, optic nerve sheath dia meter, positron emission tomography, and systemic hemodynamic monitoring includi ng heart rate variability analysis. The neurophysical basis and clinical relevan ce of each method within the ICU setting were examined. Machine learning algorit hms have shown promise by helping to analyze and interpret data in real time fro m continuous MMM tools, helping clinicians make more accurate and timely decisio ns. These algorithms can integrate diverse data streams to generate predictive m odels for patient outcomes and optimize treatment strategies. MMM, grounded in n europhysics, offers a more nuanced understanding of cerebral physiology and dise ase in the ICU."
WorcesterMassachusettsUnited StatesNorth and Central AmericaAlgorithmsCyborgsEmerging TechnologiesMachine Learning
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