Machine Learning

Epigenetic Biosignature of First-Episode Schizophrenia Identified via Machine Learning (2024)

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A new study uses AutoML and blood DNA methylation data to identify novel gene biomarkers for diagnosing schizophrenia (SCZ) with high accuracy. Highlights: Biomarker Discovery: AutoML identified three schizophrenia-specific gene methylation biomarkers: IGF2BP1, CENPI, and PSME4. Methylation Analysis: IGF2BP1 showed higher methylation and PSME4 showed lower methylation in SCZ patients compared to healthy controls, while …

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AI Algorithm Predicts Criminal Faces with ~90% Accuracy

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A 2016 study exploring whether machine learning can accurately predict criminality based solely on facial images has sparked debate on the social implications of such technology. The research, conducted by Chinese academics Xiaolin Wu and Xi Zhang, claims to be the first of its kind in using automated face recognition to categorize criminals versus non-criminals. …

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New AI Eye-Tracking Technology for Rapid Depression Diagnosis

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Depression is a growing mental health concern, especially among young adults. New AI-powered research offers a rapid, objective screening tool to identify those at high risk using eye tracking technology. This innovative approach could revolutionize early detection and intervention. Key Facts: Depression is the leading cause of disability worldwide, often starting in young adulthood. Early …

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Depression vs. Anxiety Differences: Brain Waves & Activation Patterns via Machine Learning

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Research provides new evidence that generalized anxiety disorder (GAD) and depressive disorder (DD) have distinct patterns of brain activity. Machine learning analysis of EEG data reveals signature brain features that may enable more accurate diagnosis. Key Facts: DD showed increased beta band power and complexity compared to GAD Brain network connectivity was altered in both …

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Machine Learning AI Predicts Hit Songs By Analyzing Brain Activity Responses

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Scientists have developed a new way to identify hit songs that people will love by measuring listeners’ brain activity responses using machine learning AI. This approach was much more accurate than asking people if they liked each song. Key Facts: Researchers measured people’s brain activity while they listened to 24 new songs. They tracked emotional …

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AI Reconstructs Pink Floyd Music from Auditory Cortex with Decoding Models

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Researchers have reconstructed a recognizable version of the Pink Floyd song “Another Brick in the Wall” directly from recorded brain activity. Using advanced machine learning techniques, the team was able to extract enough acoustic information from listeners’ brain signals to identify the song and recreate an intelligible version. Key highlights: Researchers recorded brain activity via …

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