MSD’s Post

🔥🎙️ EPISODE IS OUT! Delve into the world of Biostatistics, Healthcare Research, and Data Science with me. From mentoring interns to bridging data science with medical breakthroughs. Join the conversation on statistical methodologies, healthcare advancements, and simplifying complex concepts. Ft. Farnoosh Sheikhi Full Episode : https://lnkd.in/dDyGbYzF 🌐📊🏥 #Biostatistics #HealthcareResearch #datasciencetraining

🚀#100DaysOfML Day 38✅ 🚀 Ever dived into the intricate world of Medical Datasets? 🧪 Managing organic structures as names, colossal datasets, and dealing with missing values in rows - it's a fascinating journey! ✨ Key Steps in the Exploration: 1. Employed Label Encoder to handle complex data structures. 2. Applied techniques like Variance Threshold for feature selection. 3. Utilized scatter plots to identify meaningful features. 4. Leveraged correlation analysis, focusing on target variables like mZagreb1 and mZagreb2. 🔍 In-Depth Exploration: - 🧠 Feature Reduction: Employed Variance Threshold, Correlation Matrix and Linear SVC methods to trim down features from 1615 to 474. - 🛠️ Data Preprocessing: Ensured data readiness through careful preprocessing steps. - ⚖️ Feature Scaling: Maintained consistency through the dataset by scaling features. 💡 Takeaway: Navigating the complexities of medical datasets demands a blend of data science tools and methods. Every step is a learning experience! 🌐💻 #MachineLearning #DataScience #MedicalData #DataExploration #FeatureEngineering

Fun discussing how #DataScience platforms and #MachineLearning can enable #PersonalizedMedicine and #DrugDiscovery! Read the free article in The Data Scientist Magazine: https://lnkd.in/e2CurYjU If you're interested in this kind of work - check out what we're building at Character Biosciences

Excited to share my latest project! I've implemented logistic regression on a diabetes dataset using machine learning techniques. Dataset: Explored the Diabetes dataset to predict the onset of diabetes based on various health factors. It was a challenging yet fascinating exploration into the correlation between these factors and the onset of the condition. Approach: Leveraged logistic regression due to its efficacy in binary classification problems. Employed feature engineering and model tuning to enhance predictive accuracy. Challenges & Solutions: Overcame hurdles such as [explain challenges], resolved through [mention solutions or approaches]. It was a valuable learning experience that refined my problem-solving skills. Results: Achieved (accuracy, precision, recall, etc.) in predicting diabetes onset, validating the effectiveness of the implemented logistic regression model. Key Takeaways: This project reinforced my understanding of machine learning techniques and their applications in healthcare analytics. Excited to continue exploring the intersection of data science and health! I'd love to hear your thoughts and insights! Let's connect and discuss further. #MachineLearning #DataScience #HealthcareAnalytics #LogisticRegression #DiabetesPrediction

Arize just shared an exciting interview with Klick Health's DS Leader, Peter Leimbigler! In the interview, he emphasized the significance of LLM Observability and explained why Klick Health loves Arize: Phoenix. Check out the interview to learn more about the importance of observability in data science and how Arize can help your organization. #observability #datascience #ArizePhoenix #KlickHealth Click link below to learn more about the interview: https://lnkd.in/gQMJBJ6q

Interested in finding out more about the how data science is impacting the life sciences industry? Please read over this weeks blog #lifesciences #datascience #statistics #clinicaltrials

Excited to dive into these insightful reads: "The Emperor of All Maladies," "Biostatistics: Foundations for Analysis in the Health Sciences," and "Ace the Data Science Interview." As I continue my journey in healthcare and data science, I'm want to transition from digital to hardcopies to immerse myself more deeply in the content. Balancing work and continuous learning is challenging but incredibly rewarding. Each book represents a step toward enhancing my expertise and becoming a Subject Matter Expert by the end of 2024. Grateful for the opportunity to grow and learn every day. #ContinuousLearning #Healthcare #Datascience #ProfessionalDevelopment

While achieving over #100citations may not seem significant, but reminds me the initial challenges to explore #Data Science domain & publish research articles in #SCI #Journals Despite not writing any research paper in the last two years, I remain committed to advancing research in the #Data Science and #GenAI fields, striving to develop scalable solutions to meet business needs.

Hello #datasciencecommunity Exciting News! Just completed a fascinating project on HEART DISEASE PREDICTION using logistic regression! Dataset Exploration: Sourced from Kaggle, I meticulously explored the dataset to understand its intricacies and uncover hidden patterns through thorough Exploratory Data Analysis (EDA). From understanding feature distributions to identifying potential correlations, every detail was scrutinized! Model Building: Armed with insights from EDA, I dived into model building using logistic regression. After carefully splitting the data into training and test sets, I trained the model and evaluated its performance. The results? An impressive 83% accuracy on the test data! Looking Forward: But why stop there? With a thirst for continuous improvement, I'm convinced that by exploring different ensembling techniques, we can elevate the accuracy even further! Comprehensive Documentation: To ensure transparency and accessibility, I've prepared a detailed documentation outlining each step of the project. From data preprocessing to model evaluation, it's a treasure trove of knowledge for aspiring data scientists! #HeartDiseasePrediction #LogisticRegression #DataScience #KaggleDataset #EDA #EnsembleTechniques #ModelEvaluation #HealthcareAnalytics #MachineLearning #DataAnalysis #PredictiveModeling #HealthTech #dataanalysis Let's keep pushing the boundaries in data science! 💡💼✨

The unique qualities of #BigData do not reflect in volume alone. Big Data is generated continuously, is flexible and fine-grained in scope. https://bit.ly/3gBIEpV #neurophilosophy