Call for Papers – Neuropsychiatric Disease and Treatment: AI and machine learning in neuropsychiatric disease diagnosis, prognosis and treatment

Cognition and psychiatry Imaging and diagnostics Journal Articles Technology and techniques

Do you have original research or review papers you wish to publish on how applications of artificial intelligence (AI), machine learning (ML) and data mining (DM) can improve the diagnosis, treatment and management of neuropsychiatric diseases? Neuropsychiatric Disease and Treatment invites you to submit your paper to its latest Article Collection entitled ‘Artificial intelligence and machine learning in neuropsychiatric disease diagnosis, prognosis and treatment’.

AI, ML and DM are transforming neuropsychiatric healthcare technologies by enabling early diagnosis, personalized treatment and improved patient outcomes. These technologies can analyze complex, multimodal data to uncover patterns that traditional methods often miss, enhancing diagnostic accuracy and treatment strategies for disorders like autism, ADHD, anxiety, depression, schizophrenia, etc. By integrating advanced techniques such as deep learning and neural networks, AI-driven approaches offer the potential to revolutionize neuropsychiatry, leading to the discovery of novel biomarkers and more effective, individualized interventions.

The Article Collection focuses on the cutting-edge applications of AI, ML and DM in the field of neuropsychiatry, and welcomes original research articles, survey papers, meta-analyses and review articles exploring various subtopics including (but not limited to):

  • AI/ML in neuropsychiatric disease diagnosis and prognosis: Studies on how AI models, including deep learning and reinforcement learning, can be used to predict disease onset, progression and therapeutic response.
  • AI/ML models for biomarker discovery: Utilizing ML algorithms to identify novel biomarkers for neuropsychiatric conditions, focusing on genetic, neuroimaging and clinical data integration.
  • Personalized treatment through AI/ML: Exploration of AI-driven approaches in tailoring treatments for patients based on their unique genetic, clinical and environmental factors.
  • Data mining techniques in cognitive disorder management: Application of advanced data mining algorithms to clinical datasets for the early detection and monitoring of conditions like schizophrenia, bipolar disorder and depression.
  • Neuroimaging and neuroinformatics in AI/ML: Development of AI/ML algorithms to analyze neuroimaging data (e.g., MRI, PET scans) for better understanding of brain structures associated with neuropsychiatric disorders.
  • Challenges and ethical considerations in AI/ML in neuropsychiatry: Addressing issues related to data privacy, ethical implications and bias in AI/ML models when applied to sensitive health data.

For further information, please review the journal Aims and Scope and Instructions for authors. The deadline for submissions is 31 January 2026.

Please reach out to Commissioning Editor Sam Zhang ([email protected]) for more information and to receive a discount on the journal’s Article Processing Charge (APC).