AIMC Topic: Smartphone

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Deep learning for brain disorders: from data processing to disease treatment.

Briefings in bioinformatics
In order to reach precision medicine and improve patients' quality of life, machine learning is increasingly used in medicine. Brain disorders are often complex and heterogeneous, and several modalities such as demographic, clinical, imaging, genetic...

Smartphone-based diabetic macula edema screening with an offline artificial intelligence.

Journal of the Chinese Medical Association : JCMA
BACKGROUND: Diabetic macular edema (DME) is a sight-threatening condition that needs regular examinations and remedies. Optical coherence tomography (OCT) is the most common used examination to evaluate the structure and thickness of the macula, but ...

A novelty route for smartphone-based artificial intelligence approach to ophthalmic screening.

Journal of the Chinese Medical Association : JCMA
Artificial intelligence (AI) has been widely applied in the medical field and achieved enormous milestones in helping specialists to make diagnosis and remedy decisions, particularly in the field of eye diseases and ophthalmic screening. With the dev...

[Artificial intelligence and smartphone program applications (Apps) : Relevance for dermatological practice].

Der Hautarzt; Zeitschrift fur Dermatologie, Venerologie, und verwandte Gebiete
ADVANTAGES OF ARTIFICIAL INTELLIGENCE (AI): With responsible, safe and successful use of artificial intelligence (AI), possible advantages in the field of dermato-oncology include the following: (1) medical work can focus on skin cancer patients, (2)...

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...

Systematic Review of Digital Phenotyping and Machine Learning in Psychosis Spectrum Illnesses.

Harvard review of psychiatry
BACKGROUND: Digital phenotyping is the use of data from smartphones and wearables collected in situ for capturing a digital expression of human behaviors. Digital phenotyping techniques can be used to analyze both passively (e.g., sensor) and activel...