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Depression at IgMin Research | Medicine Group

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Depression is a complex and pervasive mental health condition that significantly affects mood, cognition, and overall well-being. This field of study seeks to understand the biological, psychological, and social factors contributing to the onset and progression of depressive disorders. Researchers in this area explore a wide range of topics, from the neurochemical imbalances involved in depression to the impact of genetics and environmental stressors. Advancements in the understanding of depression are crucial for developing effective diagnostic tools and therapeutic interventions.

The study of Depression encompasses not only the biological underpinnings but also the psychosocial dynamics that influence mental health. By integrating insights from neuroscience, psychiatry, and cognitive-behavioral sciences, this field aims to improve therapeutic strategies, ranging from pharmacological treatments to psychotherapy and lifestyle interventions. Research in depression is vital for enhancing patient outcomes, reducing the global burden of mental illness, and promoting resilience and mental well-being.

Neurobiology of Depression Major Depressive Disorder Depression in Adolescents Treatment-Resistant Depression Cognitive-Behavioral Therapy for Depression Pharmacological Interventions Role of Neurotransmitters Genetics and Epigenetics of Depression Depression and Anxiety Comorbidity Seasonal Affective Disorder Impact of Chronic Stress Depression and Sleep Disorders Mindfulness-Based Interventions Depression in Geriatric Populations Role of Nutrition in Mental Health Exercise and Depression Depression and Inflammatory Markers Digital Therapeutics for Depression Impact of Social Support on Depression Suicide Prevention Strategies
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Research Articles
  1. Designing a Compact High-precision Positioner with Large Stroke Capability for Nanoindentation Devices
  2. Federated Learning- Hope and Scope
  3. Risks and Effects of Medicinal Plants as an Adjuvant Treatment in Mental Disorders during Pregnancy
  4. A Machine Learning-based Method for COVID-19 and Pneumonia Detection
  5. Assessment of Thermal Uniformity of Heating Plates Using a Thermal Imaging Camera
  6. Correlation between Different Factors of Non-point Source Pollution in Yangtze River Basin
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