NeuroDigital1/ PredictBrain

Discover an App which will help you and your family members to unlock your brain health in minutes delivered to your phone. No blood tests, no brain scans, no hospitals or visits to doctors are needed. The absolutely non-invasive tests in the form of regular symptom checks, mind tests and mental health tests (similar to psychological and neurological tests but easier) present you with a total brain health score, which indicates which actions to take next. This App is unique because it can read the typical pattern of early symptoms and brain health declines for each specific brain disease, such as brain cancer, and it can assess your risk individually and fast. If you have a family history of brain diseases or cancer, this might be the right early-warning app for you. But also if you want to improve and monitor your brain health regularly for other reasons or experience unexplainable diffuse symptoms which you need to check, this App can help.

today we started working on novel concept for early pediatric diagnosis app for children with brain cancer

Mai is the Brain Tumor Awareness Month, here some sad facts, which we fight by building accessible easy and fast brain health tests to predict brain diseases such as brain cancer early

of finance, Munich, Bavaria

Based in Munich Garching too

Neural Biomarker for OCD Identified

Researchers have discovered a neural activity pattern that can predict and monitor the clinical status of OCD patients undergoing deep brain stimulation (DBS).

This biomarker guides DBS therapy, enhancing treatment outcomes for severe, treatment-resistant OCD patients.

The identification of this neural signature marks a significant advancement in DBS technology, making the therapy more accessible and effective.

These findings could potentially extend to other neuropsychiatric disorders, offering new avenues for diagnosis and treatment.

Learn more: https://technet.works/LanguageComm

People Prefer AI in Fairness-Related Decisions

A new study reveals that over 60% of participants prefer AI over humans for redistributive decisions, despite rating AI decisions as less satisfying and fair.

Researchers found that participants value the potential unbiased nature of AI but emphasize the importance of transparency and accountability.

The study involved over 200 participants from the UK and Germany in an online decision experiment.

These findings highlight the need for improving algorithm consistency to boost public acceptance of AI in moral decision-making contexts.

AI Mimics Human Decision-Making for Better Accuracy

Researchers developed a neural network that mimics human decision-making by incorporating elements of uncertainty and evidence accumulation.

This model, trained on handwritten digits, shows similar accuracy, response time, and confidence patterns to humans when tested on noisy data.

The neural network’s human-like decision process could improve AI reliability and reduce cognitive burdens.

Future applications aim to further refine AI systems to better emulate human decision-making abilities.

Brain Areas Take Micro-Naps While the Rest Stays Awake

New research reveals that sleep can be detected by millisecond-long brain activity patterns, showing that small regions of the brain can take micro-naps while the rest of the brain stays awake, and vice versa.

This study challenges traditional views on sleep and wake states by uncovering high-frequency patterns that define sleep.

Using advanced neural network analysis, researchers identified these micro-naps, which could help in understanding neurodevelopmental and neurodegenerative diseases linked to sleep disturbances.

These findings provide a deeper insight into the complex dynamics of brain function.