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Task 2 completed 🎆 CognoRise InfoTech #internship Recently completed #Breast_cancer_Classification project as a part of internship at CognoRise InfoTech. The main aim was to build a machine learning model to diagnose the breast cancer using data from fine needle aspirates. The dataset contains features that describe various properties of the cell nuclei seen in the FNA images. Key Highlights 1)Data cleaning - Handling missing, removing unnecessary columns 2)EDA - data visualization, Identifying patterns 3)Model training - split data into training and testing sets, train the models using training set 4)Model evaluation - Using evaluation metrics like accuracy score evaluate the model's performance 5)Model tuning - adjust the model's hyperparameters to improve performance Models #KNN #RandomForestClassifier #DecisionTreeClassifier #LogisticRegression #LinearRegression #internship #machinelearning

As an intern at the Provo Cancer Center, I have been exposed to different types of technology that are used to benefit the medical field. One of those is the Electronic Medical Record which has transitioned the medical world. This form of technology provides up-to-date and accurate information about a patient's health and helps both the patient and the provider. Another form of technology more specific to oncology, is a drip or an IV. This is used to give chemo to patients intravenously. By using this method, the treatment can be specific to one part of the body. This may limit the effect of chemo on other parts of the body. Below is a picture of the area where chemo is given. Nebo School District CTE Internships Christine Thomas Robyn Dunn #nebointerns #nebo #cteinternships #cteintern #MMHS #mmhsintern #internships #oncology #medicine #healthcare

I'm happy to share that I have completed my task-3 Heart Disease Prediction under the guidance of Sandip Gavit and TechnoHacks EduTech Official. Task 3 : Heart Disease Prediction Dataset Used :https://lnkd.in/gnvPsK3Y This database contains 76 attributes, but all published experiments refer to using a subset of 14 of them. In particular, the Cleveland database is the only one that has been used by ML researchers to date. #TechnoHacksEduTech #SandipGavit #internship #MachineLearning

Hello Connections,   I'm Happy to share that I have completed my second task as a part of my Machine Learning Internship program TechnoHacks EduTech Official. Task 2: Heart Disease Prediction The objective of this project is to predict heart disease in patients using machine learning techniques. Patients are classified as having or not having heart disease based on cardiac catheterization, the gold standard diagnostic method. If patients have more than 50% narrowing of a coronary artery, they are labeled as having heart disease.  The dataset comprises four databases: Cleveland, Hungary, Switzerland, and Long Beach V. The "target" field indicates the presence of heart disease, with 0 signifying the absence of disease and 1 signifying its presence. By analyzing these attributes, the project aims to develop a reliable model for predicting heart disease, ultimately contributing to better diagnosis and treatment. This could potentially lead to early detection and improved patient outcomes. Thank You TechnoHacks EduTech Official Guide: Sandip Gavit #MachinLearning #Internship #HappyLearning

I'm thrilled to announce that I have successfully completed the 'ARTIFICIAL INTELLIGENCE' internship at Adaovi! It has been an incredible journey of growth and learning, and I'm grateful for the opportunity to have been a part of such an innovative team. Special thanks to Adaovi. During my internship, I had the chance to work on exciting projects, including one on Lung Cancer Classification. You can check out the project here: https://lnkd.in/dRPFciGB I look forward to applying everything I've learned as I continue to pursue my passion for AI. Onward and upward! 💡💼 #AI #Internship #Adaovi #ArtificialIntelligence

Wondering what medical school looks like?📚🏥 Here’s a breakdown of the 4-year journey: 1️⃣ First 2 years in the classroom learning physiology and pathophysiology. 2️⃣ Third year in the hospital for rotations, seeing patients. 3️⃣ Fourth year for clinical rotations, internships, and electives. Dr. Barry explains what to expect each step of the way! 🌟👩⚕️ #MedSchoolJourney #FutureDoctors #MedicalSchool #DoctorLife #MedStudent #HealthcareEducation #MedicalTraining #DrBarrySpeaks #Medicine #Inspiration #StrivePath #MyStrivePath #CollegeAdmissions #CollegeAdmission #Collegepreps

This summer, I had the remarkable opportunity to mentor Jossue Matute as part of BYU's Talmage internship program. Jossue is an exceptionally driven and passionate individual, and as he embarks on his research journey, I am confident that wherever he goes, he will be among the hardest working and most successful individuals. The Results of This Summer: Having been a BYU intern myself, I knew that a three-month internship presents certain limitations. It is a brief period, and expecting more than preliminary results is often unrealistic. With this understanding, Dr. Price and I set an initial goal for Jossue: to scale down our optimized lipid extraction method by approximately 1000-fold, aiming to make intra-tissue regional lipidomics feasible for our bulk-flow system. In just two weeks, Jossue, with invaluable assistance from other lab members, successfully achieved this reduction, and produced impressively high quality mass spec data. When Jossue completed the tasks we had initially planned, I faced a challenge: keeping him occupied for the remainder of the summer. Then it occurred to me—there was just enough time to undertake a comprehensive intra-tissue regional lipidomics study. What had once seemed like a pipe-dream now became both feasible and the most logical next step. Within a day, we restructured Jossue's summer activities, and we began extracting samples. Over the next two and a half months, leveraging two years of foundational work and the invaluable research of my predecessors, Jossue’s relentless determination led our subgroup to collect an impressive 3 terabytes of high-quality lipidomics data. This data includes relative abundance information for between 1,800 and 2,300 distinct lipid species and several hundred turnover rates, for each of 4 experimental blocks. Each mass spectrometry sample was meticulously extracted from as little as 0.1 mg of tissue and analyzed with bulk LC/MS analysis. I am confident that this data will provide critical insights into how Alzheimer’s disease affects the brain. As the summer drew to a close, the lipidomics subgroup gathered at Cinemark to celebrate our collective success. Thank you once again, Jossue; we'll miss you. #mentoring #gradschool #lipidomics #enzymeactivity #metabolomics

My reflective writing on my summer internship at the Science Team of Random42 Scientific Communication is now available online. In this article, I shared my experience as a PhD student without prior working experience in science animation and highlighted some valuable skills I acquired through the internship. I hope this is useful to fellow postgraduate students interested in exploring science career options beyond research!

Task 3:Disease prediction from medical data. Excited to share my 3rd task: a Heart Disease Prediction Model as a part of my internship with CodeAlpha .🎉 This model utilizes key health indicators such as chest pain type, cholesterol levels, and blood pressure to accurately predict the likelihood of heart disease. By leveraging advanced classification algorithms, this tool aims to support early diagnosis and proactive healthcare decisions GitHub link-https://lnkd.in/gMSE-VS8 #CodeAlpha #Internship #MachineLearning #Task3

Successfully completed an internship as a Machine Learning Intern at Tech Fortune Technologies, focusing on a project using k-NN and cross-validation for cancer classification with the Wisconsin dataset.