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Musarrat Hussain

Musarrat Hussain
UiT The Arctic University of Norway · Department of Computer Science

About

32
Publications
9,513
Reads
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298
Citations
Introduction
My research interest lies at the intersection of NLP, Large Language Models, and Prompt Engineering, with a specific focus on healthcare applications. I am particularly fascinated by the potential of LLMs to transform healthcare data management, patient interaction, and clinical decision-making. My goal is to develop innovative NLP methodologies and prompt engineering techniques that enhance the accuracy and efficiency of LLMs in interpreting and generating medical language.
Additional affiliations
September 2022 - April 2024
Kyung Hee University
Position
  • Postdoctoral Researcher
September 2016 - April 2024
Kyung Hee University
Position
  • PhD
September 2013 - September 2015
NUST College of Electrical & Mechanical Engineering
Position
  • MS Software Engineering
Education
September 2016 - August 2022
Kyung Hee University
Field of study
  • Computer Engineering

Publications

Publications (32)
Article
Full-text available
The prevalence of heart failure (HF) is increasing, necessitating accurate diagnosis and tailored treatment. The accumulation of clinical information from patients with HF generates big data, which poses challenges for traditional analytical methods. To address this, big data approaches and artificial intelligence (AI) have been developed that can...
Article
Clinical conversations between physicians and patients can provide a rich source of data, information, and knowledge. A plethora of tools and technologies have been developed to identify attributes of interest in unstructured text. However, identifying the name and correct value of an attribute, from real world data, in a timely manner is a nontriv...
Article
Full-text available
Introduction: High adherence to oral anticoagulants is essential for stroke prevention in patients with atrial fibrillation (AF). We developed a smartphone application (app) that pushes alarms for taking medication and measuring blood pressure (BP) and heart rate (HR) at certain times of the day. In addition to drug alarms, the habit of measuring...
Article
Objective: Causality mining is an active research area, which requires the application of state-of-the-art natural language processing techniques. In the healthcare domain, medical experts create clinical text to overcome the limitation of well-defined and schema driven information systems. The objective of this research work is to create a framew...
Article
Knowledge based systems have accomplished remarkable achievements in assisting evidence based decision making for complex problems. However, machine learning-driven, intelligent systems of today are dependent on the underlying knowledge model, which is acquired from domain experts, or the available datasets in a structured or unstructured format. M...
Article
Full-text available
Data, information, and knowledge processing systems, in the domain of healthcare are currently plagued by the heterogeneity at various levels. Current solutions, have focused on developing a standard based, manual intervention mechanism, which requires a large amount of human resource and necessitate realignment of existing systems. State-of-the-ar...
Article
Full-text available
Clinical Practice Guidelines (CPGs) aim to optimize patient care by assisting physicians during the decision-making process. However, guideline adherence is highly affected by its unstructured format and aggregation of background information with disease-specific information. The objective of our study is to extract disease-specific information fro...
Preprint
Full-text available
Background and Objectives: Clinical Practice Guidelines (CPGs) represent the foremost methodology for sharing state-of-the-art research findings in the healthcare domain with medical practitioners to limit practice variations, reduce clinical cost, improve the quality of care, and provide evidence based treatment. However, extracting relevant knowl...
Preprint
Full-text available
Objective: Causality mining is an active research area, which requires the application of state-of-the-art natural language processing techniques. In the healthcare domain, medical experts create clinical text to overcome the limitation of well-defined and schema driven information systems. The objective of this research work is to create a framewo...
Article
Full-text available
Chronic kidney disease (CKD) is one of the leading medical ailments in developing countries. Due to the limited healthcare infrastructure and the lack of trained human resources, the CKD problem aggravates if it is not addressed in its earlier stages. In this regard, the role of machine learning-based automated diagnosis systems plays a vital role...
Article
Full-text available
In the era of digital well-being, smart gadgets are the unobtrusive sources of acquiring information. A variety of personalized wellness applications support self-quantification based recommendations to provide wellness status for achieving personalized targets. However, these applications are unable to promote the induction of new healthy habits a...
Article
Full-text available
Automated medical diagnosis is one of the important machine learning applications in the domain of healthcare. In this regard, most of the approaches primarily focus on optimizing the accuracy of classification models. In this research, we argue that, unlike general-purpose classification problems, medical applications, such as chronic kidney disea...
Preprint
Full-text available
Automated medical diagnosis is one of the important machine learning applications in the domain of healthcare. In this regard, most of the approaches primarily focus on optimizing the accuracy of classification models. In this research, we argue that unlike general-purpose classification problems, medical applications, such as chronic kidney diseas...
Conference Paper
Clinical text classification is an indispensable and extensively studied problem in medical text processing. Existing research primarily employs machine learning and pattern based approaches to address the stated problem. In general, pattern based approaches perform better than other methods. However, these approaches commonly require human interve...
Article
The proposed Intelligent Medical Platform is a dialoguebased medical decision-making system that provides medical coaching and recommendation services, based on incremental learning methodology. The prototype demonstrates 90% accuracy for knowledge acquisition, 80% satisfaction level of user interaction with the system, and 95% accuracy for system...
Conference Paper
Full-text available
Clinical Practice Guidelines (CPGs) are an essential resource for standardization and dissemination of medical knowledge. Adherence to these guidelines at the point of care or by the Clinical Decision Support System (CDSS) can greatly enhance the healthcare quality and reduce practice variations. However, CPG adherence is greatly impeded due to the...
Chapter
Full-text available
Forms are the ordinary medium to collect data from prospective users and indirectly build a cordial relationship with them. This communication bridge can affect the user emotional reaction, whenever a user finds an unexpected error during or submitting the form. This paper presents an empirical user emotional eXperience study on wizard form pattern...
Preprint
Full-text available
This research presents a comparative analysis of single-objective and multi-objective evolutionary feature selection methods over interpretable models. The question taken in this research is to investigate the role of aforementioned techniques for feature selection on classification model's interpretability as well as accuracy. Since, feature selec...
Conference Paper
Full-text available
Clinical Decision Support System (CDSS) plays an indispensable role in decision making and solving complex problems in the medical domain. However, CDSS expects complete information to deliver an appropriate recommendation. In real scenarios, the user may not be able to provide complete information while interacting with CDSS. Therefore, the CDSS m...
Conference Paper
Full-text available
An enormous amount of research have been published related to ontology matching. The core motivation behind these researches aim to develop matching techniques that result in highly accurate ontology matching systems. However the performance (in terms of execution time) of these matching techniques is predominantly unexplored and is equally importa...
Conference Paper
Full-text available
The advent of different social networking sites has enabled anyone to easily create, express, and share their ideas, thoughts, opinions, and feelings about anything with millions of other people around the world. With the advancement of technology , mini computers and smartphones have come to human pockets and now it is very easy to share your idea...
Conference Paper
Full-text available
Importance and usage of the recommender system increases with the increase of information. The accuracy of the system recommendation primarily depends on the data. There is a problem in recommender systems, known as cold start problem. The lack of data about new products and users causes the cold start problem, and the system will not be able to gi...
Conference Paper
Clinical practice guidelines (CPGs) is one of the key knowledge resources used in medical domain. CPGs are mainly available in an un-structural and a semi-structural form. For a concrete knowledge, domain expert rigorously investigates the CPGs and convert them into a human readable and computer interpretable format. In this paper, we demonstrate k...
Conference Paper
Full-text available
One of many reasons of software project failure is requirement changes. Different requirement changes come up during different phases of software development. Managing these changes throughout the software life cycle especially at later development phases is a challenging task. Mismanaged requirement changes can also lead to failure of the project....

Questions

Question (1)
Question
 Any topic regarding Requirement Engineering, Software Analysis and Design or Software Quality Engineering will be appreciated. 

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