AIMC Topic: Middle Aged

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Functional, Anatomical, and Morphological Networks Highlight the Role of Basal Ganglia-Thalamus-Cortex Circuits in Schizophrenia.

Schizophrenia bulletin
Evidence from electrophysiological, functional, and structural research suggests that abnormal brain connectivity plays an important role in the pathophysiology of schizophrenia. However, most previous studies have focused on single modalities only, ...

Classification Techniques for Cardio-Vascular Diseases Using Supervised Machine Learning.

Medical archives (Sarajevo, Bosnia and Herzegovina)
INTRODUCTION: The World Health Organization has estimated that 12 million deaths occur worldwide, every year due to Heart diseases. Half the deaths in the developed countries are due to cardiovascular diseases. The early prognosis of cardiovascular d...

Identification of prognostic immune-related signature predicting the overall survival for colorectal cancer.

European review for medical and pharmacological sciences
OBJECTIVE: The morbidity and mortality of patients with colorectal cancer, one of the most common malignant tumors worldwide, is steadily increasing. The aim of this study was to investigate the association between prognostic immune-related gene prof...

Deep learning for prediction of colorectal cancer outcome: a discovery and validation study.

Lancet (London, England)
BACKGROUND: Improved markers of prognosis are needed to stratify patients with early-stage colorectal cancer to refine selection of adjuvant therapy. The aim of the present study was to develop a biomarker of patient outcome after primary colorectal ...

Medios- An offline, smartphone-based artificial intelligence algorithm for the diagnosis of diabetic retinopathy.

Indian journal of ophthalmology
PURPOSE: An observational study to assess the sensitivity and specificity of the Medios smartphone-based offline deep learning artificial intelligence (AI) software to detect diabetic retinopathy (DR) compared with the image diagnosis of ophthalmolog...

Characterization of Central Visual Field Loss in End-stage Glaucoma by Unsupervised Artificial Intelligence.

JAMA ophthalmology
IMPORTANCE: Although the central visual field (VF) in end-stage glaucoma may substantially vary among patients, structure-function studies and quality-of-life assessments are impeded by the lack of appropriate characterization of end-stage VF loss.