Beyond Diagnosis: Machine Learning in Prognosis, Prevention, Healthcare, Neurosciences, and Precision Medicine

Dear Colleagues,

This Special Issue will focus on the latest advancements and the transformative power of machine learning (ML) in revolutionizing every aspect of healthcare for predicting future health risks (prognosis), developing preventative measures based on individual patient data, and advancing the field of precision medicine. By exploring how ML can identify patients most susceptible to specific diseases and tailor interventions accordingly, this Special Issue aims to shift the focus from reactive healthcare to proactive prevention and personalized treatment strategies. The vast amount of data generated in healthcare settings, from electronic health records to medical images, contains latent information that can be extracted through advanced techniques and holds enormous potential.

This Special Issue focuses on how ML can unlock the power of these data through advanced techniques for their analysis and integration. This will enable clinicians and domain experts to gain deeper insights into patient conditions, predict future health outcomes, and ultimately make more informed decisions to improve patient care. Furthermore, a vital aspect of this exploration is ensuring the interpretability and explainability of ML models. By understanding the reasoning behind the predictions, healthcare professionals can confidently implement preventative measures and personalized treatment plans, ultimately leading to better health outcomes.

Additionally, this Special Issue will delve into the application of ML to psychology, psychological support, remote treatment, and the support of patients and people. The integration of ML in these fields promises to advance the understanding and treatment of mental health conditions, offering personalized and accessible care options. Moreover, the application of ML to neurosciences will be explored, aiming to uncover more profound insights into brain function and develop innovative treatments for neurological disorders.

Research contributions on diagnostic accuracy, treatment efficacy, diagnosis, healthcare delivery, drug discovery, and patient outcomes will be considered through innovative and interpretable ML methodologies or ML-powered simulations.

Contributions in the following areas are welcome:

• Novel ML algorithms and their application to specific healthcare challenges.
• Integrating various data sources (electronic health records, medical images, and genomics) with ML for improved diagnostics and prognostics.
• The application of ML in psychology, psychological support, remote treatment, and the support of patients and people, as well as its use in neurosciences to advance the understanding and treatment of mental health and neurological conditions.
• The development of explainable and interpretable ML models for building trust and transparency in clinical decision making.
• Ethical considerations and challenges associated with deploying ML in healthcare settings.
• Predictive modeling for drug–target interactions.
• The optimization of molecular simulations to enhance drug candidate selection.
• AI-driven strategies for improving pharmacokinetic and toxicology predictions.
• The integration of ML with high-throughput screening for lead optimization.

Short Summary: This Special Issue focuses on the latest advancements in machine learning (ML) and its impact on healthcare, highlighting how ML revolutionizes the ability to predict future health risks, develop preventative measures, and advance precision medicine using vast healthcare data. This issue also covers ML applications in psychology, remote patient support, and neurosciences to enhance mental health treatment, accessibility, and the understanding of brain functions. We particularly welcome contributions on diagnostic accuracy, treatment efficacy, healthcare delivery, drug discovery, and patient outcomes through interpretable ML methodologies.

Prof. Dr. Cristian Randieri
Dr. Giuseppe Tradigo
Dr. Riccardo Pecori
Dr. Jakub Mieczkowski
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Big Data and Cognitive Computing is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• personalized medicine
• medical imaging
• predictive modeling in healthcare
• bioinformatics
• genomics
• clinical decision support
• healthcare data analytics
• machine learning in drug discovery
• machine learning simulations
• interpretable machine learning
• health informatics
• patient monitoring
• ethical issues in medical AI
• ML in psychology
• psychological support
• remote treatment
• ML in neurosciences