Category: healthtech
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MLflow SHAP & Transformers
The post covers simplified MLflow projects for reproducible and reusable data science code. It details local environment setup, ElasticNet model optimization, and SHAP explanations for breast cancer, diabetes, and iris datasets. Additionally, it showcases MLflow Sentence Transformers for a chatbot and translation. This demonstrates their powerful interface for managing transformer models from libraries like Hugging…
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Health Insurance Cross Sell Prediction with ML Model Tuning & Validation
The content discusses the use of AI and Machine Learning (ML) for insurance cross-selling. It covers topics such as data preparation, model training with different algorithms, parameter optimization, and model evaluation. The study showcases the ability of ML models (HGBM, XGBoost, Random Forest) to predict cross-sell customers in the insurance sector, providing potential for improved…
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Hugging Face NLP, Streamlit, PyGWalker, TF & Gradio App
Table of Contents Streamlit/Dash/Jupyter PyGWalker EDA Demo PyGWalker and Dash — Creating a Data Visualization Dashboard In Less Than 20 Lines of Code PyGWalker Test PyGWalker Tutorial: A Tableau-Like Python Library for Interactive Data Exploration and Visualization PyGWalker: A Python Library for Visualizing Pandas Dataframes You’ll Never Walk Alone: Use Pygwalker to Visualize Data in…
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Top Fast-Growing Apps in 2023
The OKTA Business at Work report and blogs by Leon Zucchini discuss the fastest-growing and new app categories. Key trends include the growth of collaboration, communication, and travel apps, and the adoption of multi-cloud. Ten notable growing apps are Kandji, Grammarly, Bob, Notion, Prisma Access, Navan, GitLab, Ironclad, Terraform Cloud, and Figma. Emerging apps include…
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Early Heart Attack Prediction using ECG Autoencoder and 19 ML/AI Models with Test Performance QC Comparisons
Table of Contents Embed Socials: ECG Autoencoder Let’s set the working directory YOURPATH import osos.chdir(‘YOURPATH’)os. getcwd() and import the following libraries import tensorflow as tfimport matplotlib.pyplot as pltimport numpy as npimport pandas as pd from tensorflow.keras import layers, lossesfrom sklearn.model_selection import train_test_splitfrom tensorflow.keras.models import Model Let’s read the input dataset df = pd.read_csv(‘ecg.csv’, header=None) Let’s…
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Dealing with Imbalanced Data in HealthTech ML/AI – 1. Stroke Prediction
This post discusses the prediction of stroke using machine learning (ML) models, focusing on the use of early warning systems and data balancing techniques to manage the highly imbalanced stroke data. It includes a detailed exploration of the torch artificial neural network training and performance evaluation, as well as the implementation and evaluation of various…
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Using AI/ANN AUC>90% for Early Diagnosis of Cardiovascular Disease (CVD)
The project utilizes AI-driven cardiovascular medicine with a focus on early diagnosis of heart disease using Artificial Neural Networks (ANN). Aiming to improve early detection of heart issues, the project processed a dataset of 303 patients using Python libraries and conducted extensive exploratory data analysis. A Sequential ANN model was subsequently built, revealing excellent performance…
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Overview of AWS Tech Portfolio 2023
This summary focuses on the extensive capabilities of Amazon Web Services (AWS) by 2023, highlighting its 27% year-on-year growth and a net sales increase to $127.1 billion. AWS emerges as the top cloud service provider, offering over 200 services including compute, storage, databases, networking, AI, and machine learning. It is constantly expanding operations, having opened…
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90% ACC Diabetes-2 ML Binary Classifier
A study aims to develop an ML-driven e-diagnosis system for detecting and classifying Type 2 Diabetes as an IoMT application. By leveraging advanced supervised ML algorithms, the system can predict a person’s diabetes risk based on several factors, provide a preliminary diagnosis, and relay doctor’s guidance on diet, exercise, and blood glucose testing. The Pima…
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Comparison of Global Growth Stocks – 2. AZN
Summary: A comprehensive QC assessment of top growth stocks in Q1’23 was conducted, focusing on A-rated AstraZeneca PLC (AZN) in the biopharmaceutical industry. The company’s financial indicators, technical analysis, and algorithmic trading signals were analyzed. Backtesting showed a 34% profit from investing in AZN, outperforming the benchmark by 50%.
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ECG Early Warning System (EWS) in Terms of Time-Variant Deformations and Creep-Recovery Strain Tests
Featured Photo by Hernan Pauccara on Pexels Referring to an earlier stress-strain case study, the objective of this risk management project is to develop the ECG Early Warning System (EWS) based upon time-dependent viscoelastic deformations and observed creep-recovery mechanisms in the cardiac muscle. The creep-recovery test involves loading a material at constant stress, holding that…
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Biotech Genmab Hold Alert via Fibonacci Retracement Trading Simulations
SeekingAlpha: A ‘Strong Buy’ Call on Genmab. While analysts were issuing bearish calls on Danish biotech Genmab (GMAB), Seeking Alpha contributor Biologics had different thoughts. In fact, Genmab has risen about 6% for 2022 even as the broader biotech sector has shed about 27% for the year. Let’s examine the Genmab stock in terms of…
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Python Technical Analysis for BioTech – Get Buy Alerts on ABBV in 2023
Seeking Alpha urged investors to buy AbbVie (NYSE:ABBV), Vertex Pharma (NASDAQ:VRTX), Genmab (GMAB) and a range of other biotechs in 2022 long before those stocks outperformed − sometimes even as the consensus view on Wall Street suggested otherwise. Let’s examine the ABBV 2022 stock performance using mplfinance, plotly, bokeh, bqplot, and cufflinks libraries in Python. Let’s set the…
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Stock Market ’22 Round Up & ’23 Outlook: Zacks Strategy vs Seeking Alpha Tactics
Featured Photo by Pixabay Contents: Zacks Market Research 2022 has been a strong year for jobs: Commodity markets: Energy: Global Investments: In the Zacks October 2022 Chief Investment Officer (CIO) survey, the CIOs made it fairly clear how they felt about investing outside the US. Answer: not great. Corporate High Yield and Investment Grade Bonds:In…
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50 Coronavirus COVID-19 Free APIs
The COVID-19 pandemic has triggered the creation of numerous free, accessible APIs providing real-time data on the virus’s spread. With data in JSON and CSV formats sourced from reputable institutions, developers and researchers can track cases, government policies, and more for informed decision-making and analysis.
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Interactive Global COVID-19 Data Visualization with Plotly
COVID-19, caused by SARS-CoV-2 virus, has affected 227.2 million people and caused 4,672,629 deaths. The disease, first reported in Wuhan, has spread globally. Data visualization tools like Plotly and analysis of Kaggle datasets provide insights into the pandemic’s impact, with the US leading in confirmed cases and deaths. China has managed to control the spread.
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AI-Based ECG Recognition – EOY ’22 Status
Featured Photo by cottonbro studio on pexels. Electrocardiography (ECG) is the method most often used to diagnose cardiovascular diseases. The recent study demonstrates that an AI is capable of automatically diagnosing the abnormalities indicated by an ECG. In this post we will review and illustrate how AI applies to ECG analysis to outperform traditional ECG analysis.…
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99% Accurate Breast Cancer Classification using Neural Networks in TensorFlow
Breast cancer is a significant global health concern, affecting 12% of women. Machine Learning and Artificial Intelligence techniques play a crucial role in early diagnosis using image features. The study demonstrates a successful Neural Network model for breast cancer classification, achieving 98% accuracy and 98% F1-score. Multiple metrics confirm the model’s efficiency.
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The Power of AIHealth: Comparison of 12 ML Breast Cancer Classification Models
AI Health is leveraging Machine Learning (ML) and Artificial Intelligence (AI) for early diagnosis and prediction of breast cancer (BC), utilizing different ML techniques for binary classification of the disease. A comparative analysis demonstrated that Linear Regression was the most effective classifier based on various performance metrics. This research aims to integrate ML in public…
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A Roadmap from Data Science to BI via ML
The blog post presents a comprehensive roadmap to Data Science (DS), providing an overview of career prospects, the field’s intersections with Mathematics, Statistics, and Computer Science, and its business relevance. The text details the earning potential of data scientists and the steps towards becoming one, including Data Analysis, Machine Learning, and Business Intelligence. It highlights…
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