diaMentis develops a non-invasive diagnostic platform for early detection of Alzheimer's disease. Their solution analyzes biomarkers to provide personalized risk assessments, enabling timely intervention and treatment strategies.
Funding
Funding not disclosed
Founders
Product
Problem
Diagnosing mental health disorders like schizophrenia, bipolar disorder, and major depression relies heavily on subjective clinical observation, leading to potential inaccuracies and delays. The absence of objective diagnostic tools can result in misdiagnosis, delayed treatment, and increased healthcare costs.
Solution
diaMentis is developing a Software as a Medical Device (SaMD) platform that provides clinicians with an objective aid for diagnosing mental health disorders. The platform analyzes biosignatures obtained from a standard electroretinography (ERG) exam, a non-invasive assessment of retinal function. By applying proprietary algorithms and machine learning to ERG data, diaMentis aims to identify patterns indicative of specific mental health conditions. This approach offers clinicians a quantitative, data-driven tool to support earlier and more accurate diagnoses, leading to improved treatment selection and patient outcomes.
Target Audience
The primary target audience includes psychiatrists, neurologists, and other clinicians involved in the diagnosis and treatment of mental health disorders.
Features
- Non-invasive diagnostic aid based on retinal signal analysis (ERG).
- Software as a Medical Device (SaMD) platform compatible with commercially available ERG devices.
- Machine learning algorithms for pattern recognition and classification of mental health disorders.
- Objective and quantitative analysis to support clinical decision-making.
- Aims to improve the speed and accuracy of mental health diagnoses.