AIMC Topic: Machine Learning

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Predictive modeling and machine learning show poor performance of clinical, morphological, and hemodynamic parameters for small intracranial aneurysm rupture.

Scientific reports
Small intracranial aneurysms (SIAs) (< 5 mm) are increasingly detected due to advanced imaging, but predicting rupture risk remains challenging. Rupture, though rare, can cause devastating subarachnoid hemorrhage. This study analyzed 141 SIAs (101 un...

A modular fluorescent camera unit for wound imaging.

Communications biology
Advanced imaging tools are revolutionizing the diagnosis, treatment, and monitoring of medical conditions, offering unprecedented insights into live cell behavior and biophysical markers. We introduce a modular, hand-held fluorescent microscope featu...

Development of an interpretable machine learning model for frailty risk prediction in older adult care institutions: a mixed-methods, cross-sectional study in China.

BMJ open
OBJECTIVE: To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced decision-making and targeted health management in integrat...

Artificial intelligence-driven food quality prediction: Applying machine learning ensemble models for dynamic forecasting of pork pH and meat color changes.

Food chemistry
This study presents a food chemistry-driven approach to predict post-slaughter pork quality dynamics, focusing on the biochemical mechanisms governing pH evolution and meat color development over 48 h. The interconversion of myoglobin redox states an...

Advancements in Neuroanesthesia Through Artificial Intelligence.

Anesthesiology clinics
Artificial intelligence (AI) is transforming neuroanesthesia by enhancing precision and efficiency in managing patients during neurosurgical procedures. AI uses advanced algorithms and machine learning techniques to predict complications, optimize an...

Machine learning-based detection of changes in mapping the mangrove forest of the Yangon estuary, Southeast Asia.

Marine environmental research
Mangrove forests are globally acknowledged for stabilizing coastlines, reducing wave energy, and protecting coastal habitats and adjacent land uses from extreme events. However, most regions experience alarming mangrove loss against natural and human...

[AI in rehabilitation-application of artificial mental models for personalized medicine].

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
Artificial intelligence (AI) can support patient-centered care in prevention and rehabilitation. In Germany, almost 1.9 million patients were treated in rehabilitation hospitals in 2023, mostly due to musculoskeletal disorders. The success of rehabil...

Leveraging heterogeneous tabular of EHRs with prompt learning for clinical prediction.

Journal of biomedical informatics
Electronic Health Records (EHRs) depict patient-related information and have significantly contributed to advancements in healthcare fields. The abundance of EHR data provides exceptional opportunities for developing clinical predictive models. Howev...

The Impact of Machine Learning Mortality Risk Prediction on Clinician Prognostic Accuracy and Decision Support: A Randomized Vignette Study.

Medical decision making : an international journal of the Society for Medical Decision Making
BackgroundMachine learning (ML) algorithms may improve the prognosis for serious illnesses such as cancer, identifying patients who may benefit from earlier palliative care (PC) or advance care planning (ACP). We evaluated the impact of various prese...

Mitigating Opioid Dependence in Orthopaedic Surgery: Current Strategies and Future Directions.

British journal of hospital medicine (London, England : 2005)
The opioid crisis presents a significant burden to patients and healthcare systems. Orthopaedic surgery involves treating patients with significant pain demands, therefore opioid stewardship in this specialty is an important area in targeting the opi...