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Early Diagnosis

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Homecare Robots to Improve Health and Well-Being in Mild Cognitive Impairment and Early Stage Dementia: Results From a Scoping Study.

Journal of the American Medical Directors Association
OBJECTIVES: This scoping study is the first step of a multiphase, international project aimed at designing a homecare robot that can provide functional support, track physical and psychological well-being, and deliver therapeutic intervention specifi...

Acquaintance to Artificial Neural Networks and use of artificial intelligence as a diagnostic tool for tuberculosis: A review.

Tuberculosis (Edinburgh, Scotland)
Tuberculosis [TB] has afflicted numerous nations in the world. As per a report by the World Health Organization [WHO], an estimated 1.4 million TB deaths in 2015 and an additional 0.4 million deaths resulting from TB disease among people living with ...

Using artificial neural networks to select the parameters for the prognostic of mild cognitive impairment and dementia in elderly individuals.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: A huge number of solutions based on computational systems have been recently developed for the classification of cognitive abnormalities in older people, so that individuals at high risk of developing neurodegenerative dise...

Individualized prediction of psychosis in subjects with an at-risk mental state.

Schizophrenia research
Early intervention strategies in psychosis would significantly benefit from the identification of reliable prognostic biomarkers. Pattern classification methods have shown the feasibility of an early diagnosis of psychosis onset both in clinical and ...

Early Identification of Patients With Acute Decompensated Heart Failure.

Journal of cardiac failure
BACKGROUND: Interventions to reduce readmissions after acute heart failure hospitalization require early identification of patients. The purpose of this study was to develop and test accuracies of various approaches to identify patients with acute de...

Artificial intelligence in healthcare: past, present and future.

Stroke and vascular neurology
Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI ...

Early prediction of radiotherapy-induced parotid shrinkage and toxicity based on CT radiomics and fuzzy classification.

Artificial intelligence in medicine
MOTIVATION: Patients under radiotherapy for head-and-neck cancer often suffer of long-term xerostomia, and/or consistent shrinkage of parotid glands. In order to avoid these drawbacks, adaptive therapy can be planned for patients at risk, if the pred...

Early recognition of multiple sclerosis using natural language processing of the electronic health record.

BMC medical informatics and decision making
BACKGROUND: Diagnostic accuracy might be improved by algorithms that searched patients' clinical notes in the electronic health record (EHR) for signs and symptoms of diseases such as multiple sclerosis (MS). The focus this study was to determine if ...

Comparing humans and deep learning performance for grading AMD: A study in using universal deep features and transfer learning for automated AMD analysis.

Computers in biology and medicine
BACKGROUND: When left untreated, age-related macular degeneration (AMD) is the leading cause of vision loss in people over fifty in the US. Currently it is estimated that about eight million US individuals have the intermediate stage of AMD that is o...

GC-MS Metabolomics Identifies Metabolite Alterations That Precede Subclinical Mastitis in the Blood of Transition Dairy Cows.

Journal of proteome research
The objectives of this study were to determine alterations in the serum metabolites related to amino acid (AA), carbohydrate, and lipid metabolism in transition dairy cows before diagnosis of subclinical mastitis (SCM), during, and after diagnosis of...