Call for Papers

State-of-the-Art Techniques in Text Mining for Healthcare Data Analysis and Prediction

The process of searching through vast amounts of unstructured medical data and/or well-organised health records for correlations and associations between facts and data parameters in order to extract important information, supporting data, scientific discoveries, and conclusions that can advance medical practice and/or knowledge is known as healthcare data mining. Finding hidden patterns, connections, and anomalies in massive databases using statistical analysis and machine learning is known as data mining. This information can assist users in understanding complicated occurrences, forecasting the future, and making judgments. The technique of examining past healthcare data to find patterns and trends that might be indicative of future events is known as predictive analytics in healthcare, or simply "predictive analytics healthcare." A machine learning technique called text analysis (TA) is used to automatically extract insightful information from unstructured text input. Businesses utilise text analysis tools to quickly turn papers and web data into insights that can be put to use.

Text mining employs Information Retrieval (IR), Natural Language Processing (NLP), and Information Extraction (IE) techniques to analyse unstructured text data. Information retrieval techniques are employed to first isolate significant data from unstructured data. the most sophisticated and widely applied techniques in a given field, renowned for their exceptional efficacy and performance. Using the prior data as a guide, scientists must forecast the missing data for a new observation in the prediction process. Alternatively said, one could state that the predictive models build a model that can be used to forecast values for new data by using understood outcomes. Modern data analytics makes use of advanced algorithms and powerful computing capacity to reveal trends, correlations, and patterns that are concealed within intricate datasets. Neural networks and decision trees are examples of machine learning algorithms that can automatically learn from data and generate predictions or suggestions. Businesses can forecast future trends and make more educated business decisions by utilising data mining techniques and technologies.

One of the fundamental subfields of data science, data mining employs sophisticated analytical methods to extract valuable insights from large data sets. In particular, predictive modelling makes it possible to predict how the disease will progress, which helps doctors prevent health concerns such medication side effects, treatment resistance that is inherited, and noncompliance with prescribed dosages. Models for predictive analytics are made to evaluate past data, find trends, identify patterns, and utilise that knowledge to forecast future trends. Time series, clustering, and classification models are common predictive analytics models. The method of utilising data to project future results is known as predictive analytics. To identify patterns that might indicate future behaviour, the procedure makes use of statistical models, machine learning, artificial intelligence, and data analysis. The process of converting unstructured text into a structured format in order to find significant patterns and fresh insights is called text mining, often referred to as text data mining. Large textual datasets can be analysed using text mining techniques to uncover hidden links, patterns, and important topics. Articles are invited that explore State-of-the-Art Techniques in Text Mining for Healthcare Data Analysis and Prediction. Case studies and practitioner perspectives are also welcome.

Potential topics include but are not limited to the following:

Text mining for adverse drug events: the promise, problems, and state of the art.
Computational intelligence and big data analytics for cyber-physical systems.
An overview of current research on heart disease prediction systems.
The Latest Developments in Data Mining Techniques for COVID-19 Pandemic Forecasting.
Overview of data mining innovations in structural health monitoring at the cutting edge.
Computational intelligence methods for medical data classification.
Techniques, Applications, and Challenges of Text Mining in the Health Care Sector.
Researching artificial neural network developments and potential research areas.
An extensive text classification system using cutting-edge natural language processing models.
The review of ultra-precision machining employing text mining at the cutting edge.
Discovering the key topics and offering suggestions for the way forward.
A review on the use of data mining techniques for effective disease prediction.

Timeline:

Manuscript submissions due: February, 02, 2025

First round of reviews completed: April, 20, 2025

Revised manuscripts due: June, 10, 2025

Second round of reviews completed: August, 20, 2025

APC

The $650.00 USD university rate apples for submissions from currently enrolled students, and $1,150.00 USD for all others
No waivers will be granted
Papers must not exceed 10,000 words
ORCID IDs are required

Submission Details

Manuscript Preparation Details
https://blockchainhealthcaretoday.com/index.php/journal/authors-submission
A COVER LETTER MUST BE SUBMIITTED. Indicate THEME ISSUE title in letter.
Download the BHTY Manuscript Template to assist developing your paper at https://blockchainhealthcaretoday.com/index.php/journal/libraryFiles/downloadPublic/6

Submission Portal
Upload your manuscript through the journal Submission Portal at https://blockchainhealthcaretoday.com/index.php/journal/about/submissions

Note: APC will apply unless your university or organization has a Publisher Agreement on file.

Editors-in-Chief

Jennifer Hinkel, Founder & President, Sigla Sciences, and Managing Director, The Data Economics Company, USA

Umit Cali, MSc, PhD, Professor of Digital Engineering for Future Technologies, University of York, UK

LeadEditor

Dr. Jawad Khan, Assistant Professor, Gachon University, Seongnam, South Korea

Additional Theme Issue Editors

Dr. Muhammad Hameed Siddiqi, Associate Professor, Jouf University, Sakaka, Aljouf, Saudi Arabia

Dr. Tariq Rahim, Lecturer, Kingston University, Kingston, England

Dr. Shah Khalid, Assistant Professor, National University of Sciences & Technology, Islamabad, Pakistan

posted 10.22.2024

Blockchain Integration in Multimodal Medical Data Systems

Blockchain technology could serve as an infrastructure that guarantees the safe exchange of electronic health data between patients, healthcare providers, hospitals, and medical professionals. It can also address the present interoperability issues in health information systems. IoMT devices can provide real-time patient sensory data for processing and analysis in healthcare control. The confidentiality and safety of patient health data transfer remain major issues in IoMT devices across a variety of product categories. A blockchain-based system is a decentralized, freely accessible digital block system where all participating blocks are spread out globally and connected by various network configurations. It is a technology that allows records of a process to be created across numerous computers or digital devices that, without changing its subsequent procedures or actions, cannot be changed retroactively. With the use of blockchain technology, a system can possess digital products, assets, and data, as well as track the record of every transaction that has ever occurred.

In order to link people, resources, and organizations, access health records with ease, and handle and respond strategically to needs from the health environment, smart healthcare is an architecture that makes use of technologies like wearables, the Internet of Medical Things, developed machine learning methods, and wireless communication technology. Medical sensors, often identified as IoMT, are a key component of smart healthcare. Multimodal medical signals are frequently required for the diagnosis of diseases because of their complicated nature. A growing topic of interest in the scientific community is the method used to fuse multimodal signals together. A key component of smart healthcare systems, the multimodal data-driven approach finds applications in everything from analyzing diseases to triage, diagnosis, and therapy. The rapid growth of medical services employing artificial intelligence and new changes in the healthcare business have been spurred by the demands placed on the data storage and decision-making by smart healthcare systems. A great deal of multimodal data is collected and analyzed for various conclusions, assessments, and predictions to aid in decision-making and management as a result of the widespread use of Internet of Things technology; nonetheless, there is a dearth of research on data integrity and privacy, and improper protection of confidential information may have a substantial impact on the rights and benefits of data owners.

This special issue presents a blockchain-based multi-mode safe data broadcasting platform for safe patient data access and control in the IoMT. The suggested framework is successfully used to satisfy the optimized safety and confidentiality needs of healthcare data management on IoMT devices. A healthcare programmed network using blockchain technology has been able to securely generate alerts for verified healthcare professionals based on patient health data.

Potential topics include but are not limited to the following:

Blockchain-based multi-modal safe healthcare data distribution architecture for IoMT
Wearables, blockchain, and artificial intelligence combined for the management of chronic illnesses
An extensive evaluation of multimodal medical signal fusion for intelligent health systems
Edge computing combined with multimedia and multimodal sensing for customised healthcare
A combination blockchain-based platform for IoT-Healthcare multimodal data processing
An Internet of medical things for detecting stress on blockchain
Utilising blockchain to preserve the privacy and security of IoT multimodal data
An All-Inclusive Healthcare System through Blockchain Technology
A collaborative resource-aware and medical safety for wearable health technologies
Deep Learning Frameworks and Systems for Multimodal Data Interpretation
Secured medical data outsourcing using blockchain technology and data deduplication.

Timeline:

Manuscript submissions due: January 10, 2025

First round of reviews completed: March 3, 2025

Revised manuscripts due: May 10, 2025

Second round of reviews completed: July 10, 2025

Submission Details

Manuscript Preparation Details
https://blockchainhealthcaretoday.com/index.php/journal/authors-submission
A COVR LETTER MUST BE SUBMIITTED. Indicate THEME ISSUE title in letter.
Download the BHTY Manuscript Template to assist developing your paper at https://blockchainhealthcaretoday.com/index.php/journal/libraryFiles/downloadPublic/6

Submission Portal
Upload your manuscript through the journal Submission Portal at https://blockchainhealthcaretoday.com/index.php/journal/about/submissions

Note: APC will apply unless your university or organization has a Publish and Read Agreement on file.

Editors-in-Chief

Jennifer Hinkel, Founder & President, Sigla Sciences, and Managing Director, The Data Economics Company, USA

Umit Cali, MSc, PhD, Professor of Digital Engineering for Future Technologies, University of York, UK

Lead Editor

Dr. Arnold Adimabua Ojugo, Professor: Department of Computer Science, Federal University of Petroleum Resources, Effurun, Delta State, Nigeria

Additional Theme Issue Editors

Dr. De Rosal Ignatius Moses Setiadi, Informatics Engineering Department, Dian Nuswantoro University, Semarang City, Indonesia

Dr. Ayei Egu Ibor, Senior Lecturer, Computer Science, University of Calabar, Nigeria

Posted 8.31.2024

Blockchain in Healthcare Today (BHTY) is the leading international open access journal that amplifies and disseminates platform approaches and distributed ledger technology research and innovation in healthcare. The journal invites multidisciplinary researchers, engineers technologists, developers, analysts, and healthcare leaders and innovators making strides in the development and advancement of the field, to submit original research, concepts/methodologies, case use, pilot implementations, reviews, technical briefs, short reports, opinions, and Letters to the Editor. Topics in this exciting field include, and are not limited to:

Fundamentals of Blockchain and DLT for Healthcare

Theoretical contributions on Blockchain and DLT
Distributed consensus and fault tolerance solutions, including domain-specific consensus (e.g., for IoT)
Protocols and algorithms
Distributed Ledger Analytics
Tradeoffs between decentralization, scalability, performance, and security
Sharding and layer 2
Combination between Blockchain and distributed databases (e.g., IPFS)

Fundamentals of Decentralized Apps, Smart Contracts, and Chain Code

Development languages and tooling
Security, Privacy, Attacks, Forensics
Transaction Monitoring and Analysis
Collaboration between on-chain and off-chain code
Token Economy and incentives
NFT (Non-Fungible Tokens) and protocols
Distributed Trust
Oracles
Blockchain as a service
Blockchain-defined networking

Application and service cases of DLT and Smart-Contracts

Identity management (e.g., Self-sovereign Identity and Decentralized Identifiers, Open ID Connect)
Finance and payments
DeFi (Decentralized Finance)
IoT and cyber physical systems
Supply chain management
Networking, Edge and Cloud Technologies
Blockchain for Beyond 5G and 6G Technologies, Telecom Process and Operation
Blockchain and AI (e.g., for federated learning)
Services or Resources Marketplaces
Public sector Blockchain solutions and infrastructures (e.g., EBSI)
Blockchain for education, public administration, health
Results from large collaborative projects on these topics

Computing Platform

Computing theory
Computer architecture
Grid and cloud computing and systems
Distributed and parallel computing systems
Embedded computing and systems
Fault-tolerant computing and systems
Ubiquitous computing and systems
Operation systems
Secure OS and Trust OS

Networking Platform

Ad hoc and sensor network platform
Broadband communication platform
Microwave communication platform
Mobile and wireless platform
Satellite communication platform
Smart home and M2M (machine to machine) network
System and network management and troubleshooting
Software defined network

Convergence Platform

Business service platform
Business management and intelligence
Internet of things
Service innovation and entrepreneurship
Service oriented computing and applications
Social networks
Security and privacy issues in emerging platforms
Convergence security
Cyber security and digital forensics
Smart grid and its security
Financial platform

Smart Human & Media Platform

Game platform
Interaction and HCI
Scientific and big data visualization platform
Smart UI/UX platform
Virtual and augmented reality
E-Learning & U-Learning platform
Web platform
Artificial intelligence platform
Big data platform
Semantic web technology platform

Submission Details

Issue Deadlines: March 1, July 1, Novmber 1, 2024
Journal Features & Benefits: https://blockchainhealthcaretoday.com/index.php/journal/BHTY
Manuscript Preparation Details: https://blockchainhealthcaretoday.com/index.php/journal/authors-submission

posted January 1, 2024

Platform Approaches and DLT Research and Innovation in Healthcare

Healthcare leaders and innovators in platform technology are making significant strides in the development and advancement of this field, and real world practical use of frontier technologies. This accelerates diagnosis, cures, increases qualityof life, lowers the cost of care, provides more access to better health outcomes, and preventative patient-provider action - all geared toward novel approaches to solve old problems that plague the medical community.

The groundbreaking BHTY open access peer reviewed journal has announced a Call for Papers for platform approaches and DLT original research, reports, reviews, and case use to demonstrate how this field is impacting the current healthcare landscape, and future of health.

In what ways do healthcare leaders and innovators stand out in platform technology?

Interoperability: Platform technologists understand the importance of interoperability, enabling seamless data exchange and integration between systems and devices
Scalability: Successful platform technology leaders design scalable solutions that can adapt to the evolving needs of healthcare organizations
Collaboration: Multidisciplinary collaborators fill practical market needs
Patient-Centric Focus: They prioritize patient-centric care, and enable engagement, empowerment, and access to health data
Security and Compliance: They prioritize security and compliance adhering to healthcare regulations around the globe
Economic Viability: They understand the financial aspects of healthcare and work toward value purposed solutions for organizations, payors, and patients
Education and Advocacy: They educate the healthcare industry about the benefits and best practices of using new technology and approaches, ad advocate for policy and support
Adaptability: They respond to shifts in patient needs, policies, and technology trends

As innovation moves out of academia and into real world implementation, researchers and multidisciplinary stakeholders are invited to present new insights, original research, and results impacting the healthcare sector around the globe.

Research, reviews, and case use will be published in Blockchain in Healthcare Today (BHTY) - the leading international open access peer reviewed journal that amplifies and disseminates decentralized platform approaches in healthcare and distributed ledger technology research and innovations. Fields of interest include healthcare information systems, leveraging data science tools and techniques, interoperability, consent mechanisms, privacy preservation, security of health data, clinical trials management, clinical computing, cryptography, supply chain management, revenue cycle automation, immersive technologies, tokenomics, governance, regulation and policy, network technologies, and failed experiments in this expanding specialty field of research.

Indexed in

Submission Details
Upload your manuscript through the journal Submission Portal at https://blockchainhealthcaretoday.com/index.php/journal/about/submissions

Manuscript Preparation Details
https://blockchainhealthcaretoday.com/index.php/journal/authors-submission

Download the BHTY Manuscript Template to assist developing your paper at https://blockchainhealthcaretoday.com/index.php/journal/libraryFiles/downloadPublic/6

Editorial Board located at https://blockchainhealthcaretoday.com/index.php/journal/about/editorialTeam

posted September 28, 2023