Artificial intelligence (AI) has emerged as a transformative tool in the field of ophthalmology, revolutionizing disease diagnosis and management. This paper provides a comprehensive overview of AI applications in various retinal diseases, highlighti...
The American journal of emergency medicine
Mar 16, 2024
OBJECTIVE: To develop and externally validate models based on neural networks and natural language processing (NLP) to identify suspected serious infections in emergency department (ED) patients afebrile at initial presentation.
BACKGROUND: Early diagnosis of atrial fibrillation (AF) is important for preventing stroke and other complications. Predicting AF risk in advance can improve early diagnostic efficiency. Deep learning has been used for disease risk prediction; howeve...
OBJECTIVE: To evaluate whether a machine-learning algorithm (ie, the "NightSignal" algorithm) can be used for the detection of postoperative complications before symptom onset after cardiothoracic surgery.
European journal of internal medicine
Mar 14, 2024
OBJECTIVES: Steatotic liver disease is the most frequent chronic liver disease worldwide. Ultrasonography (US) is commonly employed for the assessment and diagnosis. Few information is available on the possible use of artificial intelligence (AI) to ...
Journal of the American Heart Association
Feb 23, 2024
BACKGROUND: Implantable loop recorders (ILRs) are increasingly placed for arrhythmia detection. However, historically, ≈75% of ILR alerts are false positives, requiring significant time and effort for adjudication. The LINQII and LUX-Dx are remotely ...
BACKGROUND/OBJECTIVES: Study of retinal structure based on optical coherence tomography (OCT) data can facilitate early diagnosis of relapsing-remitting multiple sclerosis (RRMS). Although artificial intelligence can provide highly reliable diagnoses...
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