Intelligent Medicine

Scope & Guideline

Revolutionizing healthcare outcomes with intelligent solutions.

Introduction

Welcome to your portal for understanding Intelligent Medicine, featuring guidelines for its aims and scope. Our guidelines cover trending and emerging topics, identifying the forefront of research. Additionally, we track declining topics, offering insights into areas experiencing reduced scholarly attention. Key highlights include highly cited topics and recently published papers, curated within these guidelines to assist you in navigating influential academic dialogues.
LanguageEnglish
ISSN2667-1026
PublisherELSEVIER
Support Open AccessYes
CountryNetherlands
TypeJournal
Convergefrom 2021 to 2024
AbbreviationINTEL MED / Intell. Med.
Frequency-
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressRADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS

Aims and Scopes

The journal 'Intelligent Medicine' focuses on the intersection of artificial intelligence and healthcare, emphasizing innovative methodologies that enhance clinical diagnostics, treatment strategies, and patient management. It aims to disseminate cutting-edge research that integrates computational techniques with medical applications to improve patient outcomes.
  1. Artificial Intelligence in Medical Imaging:
    The journal extensively covers the application of AI techniques such as machine learning and deep learning in analyzing medical images, facilitating accurate diagnostics and treatment planning.
  2. Clinical Decision Support Systems:
    Research on systems that leverage AI to aid healthcare professionals in making informed decisions based on patient data and predictive analytics is a core focus area.
  3. Predictive Modeling and Risk Assessment:
    The journal publishes studies that develop predictive models for various health conditions, utilizing patient data to assess risks and outcomes effectively.
  4. Telemedicine and Digital Health Technologies:
    Emerging trends in telemedicine, particularly the integration of AI to enhance remote patient monitoring and care, are prominent in the journal's scope.
  5. Interdisciplinary Approaches to Healthcare Challenges:
    The journal encourages interdisciplinary research that combines insights from computer science, data analytics, and clinical practices to address complex health issues.
Recent publications in 'Intelligent Medicine' reveal several emerging themes that reflect the journal's evolving focus. These trends indicate significant areas of growth and interest within the field.
  1. Advanced Machine Learning Techniques:
    There is a growing emphasis on sophisticated machine learning methodologies, particularly in areas like image classification and predictive modeling for various diseases.
  2. Integration of Big Data in Healthcare:
    The use of big data analytics is increasingly prominent, with research focusing on harnessing large datasets to improve patient outcomes and healthcare delivery.
  3. Ethical Considerations in AI Applications:
    A rising interest in the ethical implications of AI in medicine is evident, highlighting the need for responsible use of technology in clinical settings.
  4. Personalized Medicine through AI:
    The trend towards personalized healthcare solutions powered by AI algorithms is gaining traction, emphasizing tailored treatment plans based on individual patient data.
  5. Telehealth Innovations:
    With the expansion of telemedicine, there is a notable increase in studies exploring AI's role in enhancing remote healthcare delivery and patient engagement.

Declining or Waning

While 'Intelligent Medicine' continues to evolve, certain themes from previous years appear to be declining in prominence. This section highlights those topics that have seen a reduction in published research or interest.
  1. Traditional Diagnostic Methods:
    There is a noticeable decline in publications focusing solely on traditional diagnostic methods without the integration of AI or advanced computational techniques.
  2. General Reviews without Novel Insights:
    The journal has shifted away from broad literature reviews that do not contribute new insights or methodologies, favoring original research and innovative applications.
  3. Non-AI Based Health Interventions:
    Research focusing on health interventions that do not incorporate AI technologies is becoming less frequent, as the field increasingly prioritizes AI-driven solutions.
  4. Basic Epidemiological Studies:
    Studies that merely describe epidemiological trends without leveraging AI for predictive or analytical purposes are less common, indicating a shift towards more advanced analytical frameworks.

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