healthcare capstone project upgrad

🏥👩🏽‍⚕️ Data Science Course Capstone Project - Healthcare domain - Diabetes Detection

This is comprehensive project completed by me as part of the Data Science Post Graduate Programme. This project includes multiple classification algorithms over a dataset collected on health/diagnostic variables to predict of a person has diabetes or not based on the data points. Apart from extensive EDA to understand the distribution and other aspects of the data, pre-processing was done to identify data which was missing or did not make sense within certain columns and imputation techniques were deployed to treat missing values. For classification the balance of classes was also reviewed and treated using SMOTE. Finally models were built using various classification algorithms and compared for accuracy on various metrics.Lastly the project contains a dashboard on the original data using Tableau.

You can view the full project code on this Github link

Note: This is an academic project completed by me as part of my Post Graduate program in Data Science from Purdue University through Simplilearn. This project was towards final course completion.

Bussiness Scenario

This dataset is originally from the National Institute of Diabetes and Digestive and Kidney Diseases. The objective of the dataset is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset. Several constraints were placed on the selection of these instances from a larger database. In particular, all patients here are females at least 21 years old of Pima Indian heritage.

Build a model to accurately predict whether the patients in the dataset have diabetes or not.

Analysis Steps

Data cleaning and exploratory data analysis -.

There are integer as well as float data-type of variables in this dataset. Create a count (frequency) plot describing the data types and the count of variables.

Check the balance of the data (to review imbalanced classes for the classification problem) by plotting the count of outcomes by their value. Review findings and plan future course of actions.

We notice that there is class imbalance . The diabetic class (1) is the minority class and there are 35% samples for this class. However for the non-diabetic class(0) there are 65% of the total samples present. We need to balance the data using any oversampling for minority class or undersampling for majority class. This would help to ensure the model is balanced across both classes.We can apply the SMOTE (synthetic minority oversampling technique) method for balancing the samples by oversampling the minority class (class 1 - diabetic) as we would want to ensure model more accurately predicts when an individual has diabetes in our problem.

Create scatter charts between the pair of variables to understand the relationships. Describe findings.

We review scatter charts for analysing inter-relations between the variables and observe the following

Perform correlation analysis. Visually explore it using a heat map.

Observation : As mentioned in the pairplot analysis the variable Glucose has the highest correlation to outcome.

Model Building

Note: ROC (Receiver Operating Characteristic) Curve tells us about how good the model can distinguish between two things (e.g If a patient has a disease or no). Better models can accurately distinguish between the two. Whereas, a poor model will have difficulties in distinguishing between the two. This is quantified in the AUC Score. Final Analysis Based on the classification report:

Data Reporting

Tools used:

This project was completed in Python using Jupyter notebooks. Common libraries used for analysis include numpy, pandas, sci-kit learn, matplotlib, seaborn, xgboost

Further Reading

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💬⚙️ NLP Project - Phone Review Analysis and Topic Modeling with Latent Dirichlet Allocation in Python

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MMHC Capstone Strategy Project

The Capstone Project engages teams of students on projects of significant importance to their organizations. The student team is responsible for diagnosing the critical problem, defining an appropriate scope of work, managing institutional expectations, and producing a suitable recommendation in both written and presentation form.

Your Capstone Team

It takes many managers, healthcare practitioners and other executives to care for a patient and to manage a healthcare organization. Having the skills to manage a team, evaluate critical problems, and execute solutions is required to be an effective business leader. This is why your Capstone Team will be comprised of a cross-functional group of 4-5 executives, each with a diverse set of backgrounds and industry experiences, giving you an experience that emulates the work environment of a healthcare delivery organization. Support includes coaching on team dynamics and the progress of your work together, checkpoints to ensure you’re on track, and guidance for projects that serve as a real-world learning lab.

The Project

The Capstone Strategy Project complements the classroom instruction and is defined as learning by construction. It is a total immersion experience in which students are challenged to use all of the tools and concepts learned to date to tackle a current business problem for a healthcare organization.

With faculty oversight, you demonstrate rigorous application of business concepts and disciplines. Leading a project of utmost importance for your organization provides immediate impact that benefits the student and the sponsoring organization.

Your team will kick off the Capstone Strategy Project in Mod 3 by meeting with the client sponsor to outline and discuss the initiative at hand. Your team will spend the next six months working on all aspects of the project, including:

I learned so much about the health care business model, and I hope to use it to improve processes across all segments of health care. Cara Anderson, Master of Management in Health Care, 2021

The Benefits For You

For the students, the Capstone Strategy Projects are opportunities to exhibit the healthcare business management knowledge you’ve acquired. You will demonstrate, to yourself and your organization, your ability to problem-solve creatively, make strategic decisions, and manage as part of a high-level executive team. Learn More .

The Benefits for Your Organization

For an organization, the Capstone Strategy Projects is an opportunity to have a team of experienced mid-level health care professionals conduct an intense engagement to address a current business need.  Learn More .

See how MMHC students' capstone helped improve Emergency Department wait times and efficiency at VUMC.

How MMHC benefits your organization

A closer look at the program through the eyes of students, faculty and sponsoring organizations

Biomedical Graduate Education

Capstone Projects

2022-2023 graduates, nelson moore.

Data Scientist at Essential Software Inc

Capstone Project: Modeling and code implementation to support data search and filter through the NCI Cancer Data Aggregator Industry Mentor: Frederick National Lab for Cancer Research: FNLCR

Joelle Fitzgerald

Business Analyst at Ascension Health Care

Capstone Project: Analysis of patient safety event reports data. Industry Mentor: MedStar Health. National Center for Human Factors in Healthcare

Kader (Abdelkader) Bouregag

Healthcare Xplorer | Medical Informatics at Genentech (internship)

Capstone Project: Transforming the Immuno-Oncology data to the OMOP CDM Industry Mentor: MSKCC/ MedStar/ Georgetown University/ Hackensack

Junaid Imam

Data Scientist at Medstar Institute

Capstone Project: Create an [trans-] eQTL visualization tool

Industry Mentor: Pfizer Inc / Harvard

Abbie Gillen

Staff Data Analyst at Nice Healthcare

Capstone Project: Nice Healthcare: Predicting Nice healthcare utilization

Industry Mentor: Nice Healthcare

Capstone Project: Next Generation Data Commons

Industry Mentor: ICF International

2021-2022 Graduates

Ahson saiyed.

NLP Engineer/Data Scientist at TrinetX

Capstone Project : Research Data Platform Pipelines Industry Mentor: Invitae

Walid Nashashibi

Data Scientist at FEMA

Capstone Project: Xenopus RNA-Seq Analysis to Understand Tissue Regeneration Mechanisms Industry Mentor: FDA

Tony Albini

Data Analyst at ClearView Healthcare Partners

Capstone project: Data Mining to understand the patient landscape of Chronic Kidney Disease Population Industry Mentor: AstraZeneca

Anvitha Gooty Agraharam

Business Account Manager at GeneData

Capstone Project: Computational estimation of Pleiotropy in Genome-Phenome Associations for target discovery Industry Mentor: AstraZeneca

Natalie Cortopassi

Researcher at the Institute for Health Metrics and Evaluation

Capstone project: Analysis of Clinical Trial Attrition in Neuropsychiatric Clinical Trials using Machine Learning Industry Mentor: AstraZeneca

Christle Iroezi

Business System Analyst at Centene Corporation

Capstone project: Visualize Digital HealthCare ROI Industry Mentor: MedStar Health

R & D Analyst II at GEICO

Capstone project: Heat Waves and Health Outcomes Industry Mentor: ICF

Research Specialist at Georgetown University

Capstone project: Mental Health Data Commons Industry Mentor: ICF

2020-2021 Graduates

Technology Transformation Analyst, Grant Thornton LLP

Capstone Project: Research Data Platform Pipelines Industry Mentor: Invitae

Research Technician at Georgetown University

Capstone Project: Using a configurable, open-source framework to create a fully functional data commons with the REMBRANDT dataset Industry Mentor: Frederick National Lab for Cancer Research – FNLCR

Consultant at Deloitte

Capstone Project: Building a patient centric data warehouse Industry Mentor: Invitae

Marcio Rosas

Project Manager of Technology and Informatics at Georgetown University

Capstone Project: Knowledge-Based Predictive Modeling of Clinical Trials Enrollment Rates Industry Mentor : AstraZeneca

Yuezheng (Kerry) He

Data Product Associate at YipitData

Capstone Project: ClinicalTrials2Vec – Accelerating trial-level computing using a vectorized model of clinical trial summaries and results Industry Mentor: AstraZeneca

Data Programmer at Chemonics International

Capstone Project: Multi-scale modeling to enable data-driven biomarker and target discovery Industry Mentor: AstraZeneca

2019-2020 Graduates

Pratyush tandale.

Informatics Specialist I at Mayo Clinic

Capstone Project: Improving clinical mapping process for lab data using LOINC Industry Mentor: Flatiron Roche

Shabeeb Kannattikuni

Senior Statistical Programmer at PRA Health Sciences (ICON Pl)

Capstone Project: NGS Data Analysis for the QA of viral vaccines Industry Mentor: Argentys Informatics

Fuyuan Wang (Bruce)

Software Engineer at Essential Software Inc , Frederick National Labs

Capstone Project: Cancer Data Model Visualization framework Industry Mentor: Frederick National Laboratory for Cancer Research

Ayah Elshikh

Capstone Project: NGS Data Analysis for the QA of viral vaccines

Industry Mentor: Argentys Informatics

Yue (Lilian) Li

Biostatistician and Statistical Programmer , Baim Institute for Clinical Research

Capstone Project: Analysis of COVID-19 Serological test data to improve the COVID-19 Detection capabalities Industry Mentor: Argentys Informatics

Algorithm Performance Engineer at Optovue

Capstone Project: Socioeconomic factors to readmissions after major cancer surgery Industry Mentor: Medstar Health

Jiazhong Zhang

Management Trainee at China Bohai Bank

Jianyi Zhang

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Stanford Online

Ai in healthcare capstone.

SOM-XCHE0012

Stanford School of Medicine , Stanford Center for Health Education

When a person develops respiratory symptoms and suspects COVID-19, what do they do? In situations such as that, how can the availability of data and its specific usage affect the diagnosis, treatment, and overall patient journey? In the capstone project, you will take a guided, interactive tour through the patient journey to see how different decisions can create different datasets and outcomes, and how regulatory and ethical limitations affect its process. With hands-on experience in the position of a medical data miner, you’ll see how data has the power to transform patient care.

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Healthcare Systems Engineering Capstone Project - 655.800

This course provides the experience of applying systems engineering principles and skills learned in the formal courses to a specific practical healthcare system project that is suggested by the student and is presented in a formal proposal. The product of the system project is a final report; also required are interim reports and an oral presentation to permit review of the project objectives and approach. A student typically has a mentor who is a member of the Systems Engineering faculty. The program chair and mentor review proposals and reports. The total time required for this course is comparable to the combined class and study time for the formal courses (formerly 645.770). It is self-paced and often takes more than one semester to complete.

Course Prerequisite(s)

EN.655.769 Healthcare System Test and Evaluation and completion of at least 3 of the four required electives and permission of course instructor.

Course Offerings

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• MPH 580 Public Health and Health Education Internship

MPH 590 Public Health and Health Education Capstone

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MPH Handbook

This graduate-level course will focus on the written explanation of the project the student completed during MPH590. The opportunity to demonstrate knowledge of essential theory, incorporate research findings, and demonstrate scholarly thought will be the emphasis of this course. This project-based capstone is designed to encourage the student to draw upon knowledge and experience gained over the course of the entire MPH program and during the public health internship. The capstone course is intended for the student to explain and defend a substantial original applied project of your own authorship.

Course Learning Objectives (CLOs):

After this course, you will be able to:

• Synthesize knowledge acquired from other public health coursework and formulate an original, comprehensive project proposal on a topic of public health interest.
• Conduct a comprehensive analysis of the literature to support the research proposal. 
• Design an implementation plan that integrates knowledge of theories, principles, methodologies, and processes to evaluate the research proposal. 
• Disseminate significant components of the project through a written paper and oral presentation, relating in detail the design, implementation, results, and conclusions of the capstone project.
• Apply the scientific rigor of the American Psychological Association's publication guidelines to research report preparation.
• Defend a public health capstone project.

Prerequisites

MPH501 Public Health in America

MPH503 Health Policy & Ethical Issues in Public Health

MPH505 Public Health Education & Program Oversight

MPH510 Epidemiology in Public Health

MPH520 Disaster Management & Emergency Preparedness

MPH530 Environmental Issues in Public Health

MPH540 Public Health Administration

MPH550 Health Behavior and Health Education

MPH560 Applied Biostatistics for Public Health

MPH570 Evidence-Based Practice in Public Health

MPH580: Public Health and Health Education Internship

All MPH students will complete MPH 590: Capstone Experience in their final semester of the program. MPH 590: Capstone Experience serves as students’ culminating experience where students will utilize the information acquired from previous public health courses and internship to design, carry out, and present a scholarly project through a paper and poster presentation.

Options for Your Capstone Project

Research project:  Students conducting a research project will identify a problem to be studied, review the literature associated with the problem, collect data about the problem (quantitative &/or qualitative), analyze the data in order to either support or refute a pre-selected hypothesis or answer research questions, discuss the findings, present conclusions, and make recommendations based on the study. The resultant paper should be suitable for publication.

Grant proposal:  Students writing a grant proposal for a public health initiative will identify the problem for which the grant would be used, explain the significance, list the hypotheses/questions to be answered, review the literature associated with the problem, create goals and objectives, methods, create a timeline and budget, and explain how the intervention would be evaluated. The resultant paper should be suitable for submission.

Other project:  This category is an all-inclusive section for projects such as community outreach reports, evaluation of an intervention or interventions, policy analysis, evaluation of an existing program, written plan for a program or a manual. This list is not exhaustive, and the program will consider any projects that result in scholarly work.

Goals and Objectives

Upon completion of this course successful students will:

• Compose a scholarly project
• Identify appropriate literature through the use of varied library resources, public-domain repositories and Internet search engines to support their scholarly project.
• Develop and organize complex ideas in a logical, orderly and well-written fashion.
• Critique limitations while creating scholarly work.
• Develop enhanced written and oral communication skills.
• Interpret reviewer feedback and defend scholarly work.

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Penn College News

Nursing students' capstones present clinical research

Thursday, April 25, 2024

Photos by Jennifer Cline, writer/magazine editor

Penn College nursing students presented their capstone projects on Tuesday, researching a variety of health conditions they saw while completing clinical education experiences in area hospitals, and exploring ways to improve a process they witnessed.

The 23 students – all preparing to complete their bachelor’s degrees after final exams next week – are enrolled in three courses that, in tandem, resulted in their capstone projects: Adult Health Nursing III, taught by Pamela W. Baker, associate professor of nursing (with labs co-taught at clinical sites by Baker and nursing instructors Gina L. Bross, Jessica A. Confer and Steve C. Sofopoulos); Leadership & Management in Nursing, taught by Donnamarie Lovestrand, assistant professor of nursing; and Research & Theory in Clinical Practice, taught by Barbie D. Harbaugh, assistant professor of nursing.

As the nursing industry – like others – seeks continuous improvement, the research, leadership and presentation skills practiced will be vital in the students’ work.

Four student groups addressed:

Research: Preventing Skin Breakdown Using Wedges vs. Pillows in Intubated Intensive Care Unit Patients Process improvement: Improve communication and team building by instituting shift huddles Students: Monica I. Boone, of South Williamsport; Hesakya Hoover, of Williamsport; Shelby Pyatt, of Frenchtown, N.J.; Miranda Schneider, of Williamsport; Kaelynn N. Sheetz, of Elizabethtown; and Allison M. Troup, of Huntingdon.  

Research: Liver Transplants with Healthy Liver vs. Liver with a Comorbidity Process improvement: Provide more education to nurses regarding organ donation Students : Felicia J. Baney, of Mill Hall; Maria Berardelli, of Montoursville; Jenna Hickok, of Williamsport; Nina Miller, of Pottsville; Austin J. Spotts, of Dalmatia; and Megan S. Twigg, of Montgomery.  

Research: Urinary Tract Infection Risk Assessment of Foley Catheters vs. External Catheters: A comparison Process improvement: Standardize the method for cleaning Foley catheters and provide consistent training to nurses Students: Madison C. Branstetter, of Tyrone; Kendra L. Rager, of Williamsport; Vanessa Reddick, of Sligo; Lisa Sever, of Montoursville; Aubrey Stetts, of Jersey Shore; and Madison S. Wells, of Muncy Valley.  

Research: Decreasing Alarm Fatigue in the ICU Setting (The alarms are those on monitoring equipment, such as ventilators and cardiac monitors.) Process improvement: Improve response time to reduce the stress of nurses and improve patient outcomes.  Students: Dana P. Clements, of Cleona; Sadie V. Kerstetter, of Loganton; Ashlyn R. Leo, of Benton; Katharine M. Noss, of Shickshinny; and Krysta Windnagle, of Addison, N.Y.

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KavithaBalamurugan/Capstone-Project-Instant-Health-Alert-System

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Capstone-project-instant-health-alert-system, problem statement.

Healthcare monitoring at hospitals has witnessed new challenges. In view of these challenges, this use case proposes a reliable data pipeline solution to store and analyse a stream of real-time data flowing from various IoT devices at hospitals and health centres. The advent of IoT devices has digitised vital health data such as body temperature, heartbeat, blood pressure (BP) and more. Capturing this high-velocity stream of data and analysing these in real-time with minimal error is only possible with the use of a robust data platform and components. This project will test your knowledge of the various tools related to data pipelining, which you learnt about throughout this course. The project revolves around Apache Sqoop, Apache PySpark, Apache Kafka, Hive, HBase, which are some of the most widely used tools in the industry.

The task in this project will be to build a solution to cater to the following requirements: Real-time alert notification system - This use case will simulate the streaming vital data of patients and building of a data pipeline to monitor vital data to alert the subscribers in real-time based on reference data. If the vital information coming from the patient is out of the normal threshold range, an alert notification will have to be sent immediately to the registered Email-ID.

At the industry level, a pipeline similar to the one showed below is used for this purpose.

Pipeline Broadly, you will be performing the following tasks in this project:

Taking streaming data (patients vital information) and storing it in a table

Taking batch data (patients contact information) and storing it in a table

Comparing the vital information with threshold information and analysing

Sending notifications if the data is out of the threshold limits