Page 324 - Emerging Trends and Innovations in Web-Based Applications and Technologies

International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
Ø Cardiovascular Diseases (CVDs): Includes heart attacks, Reliability: Reduces false alarms in health monitoring.
strokes, and hypertension. Leading cause of death
globally. Interpretability: Simplifies downstream analysis, making
results actionable for healthcare providers.
Ø Diabetes: A metabolic disorder characterized by high By carefully implementing these steps, health monitoring
blood sugar levels due to insulin issues.
systems can process raw data efficiently and provide
Ø Cancer: Uncontrolled growth of abnormal cells in the accurate insights for healthcare decisions.
body, with many types like lung, breast, and colon Disease Detection
cancer.
Disease detection is the process of screening, diagnosing, and
Ø Chronic Respiratory Diseases: Includes asthma, chronic then tracking the progression of an illness or condition and
obstructive pulmonary disease (COPD), and bronchitis. effectiveness of a treatment. It is frequently used for chronic
illnesses such as cancer but can be utilized for any disease
3. Genetic Disorders that requires consistent care. Disease detection is used to
These are caused by abnormalities in an individual’s DNA. identify a condition and during treatment of an illness. Being
Ø Sickle Cell Disease: A blood disorder leading to able to accurately detect disease and then monitor the
abnormally shaped red blood cells.
effectiveness of a treatment is crucial for effective care. Early
Ø Cystic Fibrosis: Affects the lungs and digestive system detection and treatment can help control a disease’s
due to thick mucus buildup. progress, reduce symptoms, and improve the quality of life
for people with many illnesses. Disease detection and
Ø Huntington's Disease: A progressive brain disorder monitoring is generally used if you are experiencing
causing uncontrolled movements and cognitive decline.
symptoms of an illness or undergoing prolonged treatment.
4. Mental Health Disorder In the case of screening tests, the goal is to detect an illness
These affect mood, thinking, and behaviour. early so that treatment can begin as soon as possible.
Ø Depression: A common disorder characterized by Screening tests are often used to determine if additional
persistent sadness and loss of interest. diagnostic testing is necessary. There are many different
types of diagnostic tests and methods of monitoring a
Ø Anxiety Disorders: Includes generalized anxiety disease over time. The tests and methods used in your case
disorder, panic disorder, and phobias.
will vary based on your age, overall health and medical
Ø Schizophrenia: A severe mental disorder causing condition, as well as the treatment your health care provider
distorted thinking and perception. prescribes.
Data Pre-processing Results
Data preprocessing is a critical step in developing health A health monitoring system focuses on analysing and
monitoring systems as it ensures that raw data collected improving healthcare services for individuals or populations.
from sensors, medical devices, or user inputs is clean, Its results typically include:
consistent, and ready for analysis. The primary goal is to 1. Improved Health Outcomes:
improve data quality and prepare it for machine learning Ø Better management of chronic diseases (e.g., diabetes,
algorithms or statistical analysis.
hypertension).
Sources: Data is collected from wearable devices, IoT Ø Timely identification of health risks or conditions.
sensors, medical imaging, electronic health records (EHR), or
manual inputs. 2. Data Insights and Trends:
Ø Consolidated patient records with insights into medical
It may include physiological signals (heart rate, blood history, results and treatments.
pressure, temperature), activity logs, demographic
information, or environmental conditions. Missing data is Ø Predictive analytics for anticipating health events or
common in health monitoring (e.g., due to device outbreaks.
malfunction or user non-compliance).
3. Enhanced Preventive Care:
There are some techniques include for fixing this issue i.e. Ø Personalized recommendations for lifestyle changes.
Imputation (mean, median, or advanced methods like k-NN) Ø Medication reminders or routine health check-up alerts.
& removing incomplete records (if the missing data is
minimal). Physiological data often has outliers due to input 4. Operational Efficiency:
errors or anomalies. Statistical methods like z-scores or IQR Ø Reduced duplication of tests and medical errors through
can identify these. Signals such as ECG or PPG may contain integrated systems.
noise from motion artifacts or environmental interference. Ø Streamlined communication between healthcare
Filters (e.g., Butterworth or moving average) are applied to providers and patients.
denoise. If data comes in different units (e.g., Celsius vs.
Fahrenheit), it should be converted to a consistent format. If 5. Cost Reduction:
data includes categories (e.g., gender, disease type), these Ø Lower healthcare expenses by focusing on preventive
need to be encoded as numeric values. Ensuring processed measures.
data maintains integrity and consistency. This involves visual Ø Efficient resource allocation for treatments.
inspection, statistical checks, or running basic analytics.
In essence, a health monitoring system aims to ensure better
Importance of Preprocessing
Model Accuracy: Cleaner and standardized data improves the care coordination, improve individual health outcomes, and
optimize healthcare resources.
performance of predictive models.

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