Natural Language Processing(NLP) And Process Modeling In Precision Medicine
Natural language processing system poses a huge impact and opportunities in healthcare and precision medicine through the massive availability of unstructured data and leverage on it to improve and optimize the performance and practice of precision medicine. Natural language processing is one of the main branches of Artificial intelligence that deals with the translation of human language and continues to play a big role in the major and strategic aspects of our lives.
The advent of natural language processing system applications such as speech recognition, urgency detection,auto-correct, machine translation, chatbot/virtual assistant, and sentiment analysis has a potent impact on our day to day activities, applications such as google translate; a machine translation that translates different languages into user respective and preferred language, Alexa virtual assistant that is capable of voice interaction and controlling several smart devices making it a home automation system, and the most notable auto correct in our mobile devices that correct and propose changes and correction to words or misspelled words.
The acceptance of NLP in healthcare is accelerating because of its ability in comprehending human language, processing unstructured data, mapping out important information, and extracting key concept and meanings which provides simplicity to healthcare practitioners in interpreting, analyzing, and searching large bulk of clinical data into more accurate, qualitative and understandable form thus giving more preciseness and accessibility into the medical records.
Due to the availability of large unstructured data, NLP taps into this advantage to interpret, process medical record data into a more concise and reasonable format that helps medical practitioners and researchers in their field of research and clinical domain.it also provides treatment and medical terms that enhance strategic and effective healthcare data mining and give profound insight into the Electronic Health Record(EHR).
In precision medicine, the prevention and treatment of disease take into account the patient variability in genes, lifestyle, and environment for each person.
Precision medicine is a medical model that proposes the customization of healthcare, with medical decisions, treatments, practices, or products being tailored to a subgroup of patients, instead of a one‐drug‐fits‐all model. Wikipedia
Precision medicine proposes a tailored and personalized medical decision and treatment to select the best approach that is most suitable and likely to helps the patient based on the patient’s medical data.
NLP application in Precision medicine:
1-research and mapping out health disparities:
Due to the availability of massive medical data, researchers uses natural language processing system to find health differences of ethnic and racial groups, their resistance and susceptibility to certain treatments and disease, this information provides advanced knowledge, cohesive and significant approach to clinical decision, research, biomedical and drugs company.
2-improve time efficiency:
Natural language processing system reduced stress, manual inspection, analysis, and interpretation of large amount of medical record thereby providing more free time to the medical practitioners to focus on other works.
3-enhancing treatment effectiveness and approach
NLP is used for disease treatment by providing a better and effective approach for the treatment of patients in consideration of the medical records and conditions.
with enough medical information, NLP can predict health risks and approaches that are most likely to mitigate the spread of the disease.
3-clinical decision-making support:
Natural language processing systems help medical practitioners to evaluate and make important decisions in different areas of clinical practice such as disease diagnoses and treatments which helps in reducing time-consuming processes and errors in medical decisions.
A process is a set of recipes, related tasks, or activities that are carried out to achieve a particular result.
Process modeling is used to describe the process of a task by diagrammatically displaying the steps and activities of the process, it briefly manifests the actions and precedence of the task, For example, a diagram that represents
how to deliver healthcare from the patient’s contact with the doctor, the medical evaluation, recommendation, and to the required treatment.
Healthcare processes are complex and dynamic, co-ordinating such a process is a very difficult and intricate task, process modeling enables us to organize and fully understand the best dimension of healthcare for patients with a particular medical condition and how to stratified such healthcare pathways for different types of patients and also how to improve the provisional healthcare services.
There are many languages for process modeling, some of the languages are:
1. Business process modeling notation (BPMN)
3. Flow chart technique
4. Data flow diagrams
5. Gantt charts
Business process modeling notation (BPMN)
BPMN is one of the most popular modeling languages and basically designed for business professionals, but it is currently in use in different sectors.
It is widely used to efficiently optimize processes such as business and healthcare process, it helps in identifying challenges in our current systems thus providing us with an opportunity to evaluate all the steps and procedures and give us a diagrammatic visualization and pathway of the process so that we can improve the analysis and understanding of the task.
After modeling a process, we need to analyze to see how the healthcare procedures are organized, we do this by analysis process, this process gives a profound insight into how medical steps and procedures are being carried out.
there are two main approaches to the analysis process, they are:
This process proves or disproves the correctness and validity of the process model for certain properties.it involves the analysis that was gathered throughout the design and manufacturing of a product so that to verify if the process can reliably output products of a specific standard. This process is essential in determining product quality, it is the process of determining if a model implementation and its associated data accurately represent the developer’s conceptual description and specifications. It determines the degree to which a simulation and its associated data are an accurate representation of the real world from the perspective of the intended uses of the model.
It is used in analyzing the performance of a process by imitating a future or real-world process. In this process, a healthcare task is produced with some factors that will enable prediction and analysis so that to be prepared for any expected and unanticipated case and to better improve decision-making and optimization of the process. Simulation models are being used to solve problems and to aid clinical decisions in healthcare and throughout the development of a model.
It is the systematic method of designing and discovering processes that involve massive data collection.it involves different techniques such as tapping into the medical health record, observation, interview, research, and simulation to find the effective system of designing a productive process.
Process mining is a family of techniques relating the fields of data science and process management to support the analysis of operational processes based on event logs. The goal of process mining is to turn event data into insights and actions. Wikipedia