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The Theory of Planned Behaviour predicts consumer behavior better when emotions, personality, demographics, and marketing are included.

New models predict male pattern baldness better than old ones but still need improvement.

The model helps understand alopecia areata and suggests treatment strategies.

The document explains how to measure sales and marketing success and warns about misusing these measurements.

The method effectively predicts new drug uses, including potential COVID-19 treatments.

Pattern mode isolation improves the reliability and predictability of Turing patterns.

The method accurately predicted stock price changes, showing most companies' returns decreased due to BDS actions.

The system can have a stable solution under certain conditions, helping understand hair loss in Alopecia Areata.

Sparse hairless patches can develop and stabilize in alopecia areata under certain conditions.

Choosing the right model order in brain connectivity analysis can affect the detection of differences between healthy individuals and those with seasonal affective disorder.

The model improves understanding of androgen interactions by focusing on signal intensity and system capacity.

Large language models can accurately identify monkeypox from medical records.

The new method provides more accurate vibrational frequencies for drug molecules than traditional models.

A new method accurately measures molecular movement without complex modeling.

Mitochondrial genes help predict breast cancer outcomes and spread.

The model showed that immune system guardians and the cytokine interferon-γ are key in alopecia areata progression.

Marxan is better for designing Marine Protected Areas in the Eastern English Channel.

The model improves understanding of androgen interactions by focusing on signal intensity and system capacity.

The model successfully predicted new uses for existing drugs, like using certain hormonal and heart medications for respiratory and Parkinson's diseases, and a cancer drug for diabetes.

A new method accurately measures college students' mental health by considering time perception and clustering techniques.

The model helps understand alopecia areata and suggests ways to improve treatment by targeting immune issues.

The conclusion is that balancing cost and carbon emissions in hybrid power systems is crucial, especially when high reliability is needed, but the model needs to consider all device efficiencies and distribution losses.

The EMG-to-force model accurately predicts hip muscle forces during walking.

The document suggests a new model for evaluating public research that better captures the full value of knowledge creation and use, using PCOS research as an example.

Machine learning can predict how well patients with alopecia areata will respond to certain treatments.

The model showed that randomness accurately describes individual hair growth cycles and that synchronization can cause large fluctuations not seen in humans.

The model accurately predicts hair loss by analyzing various factors.

The document concludes that computational models are useful for understanding immune responses and could improve cancer immunotherapy.

AI can effectively predict COVID-19 mortality risk using patient data.