• Projects 5
  • Rating 4.7
  • Rating 564

Budget: 3000 UAH Deadline: 4 days

Hello! I am engaged in data analysis using Python — I have calculated correlations and built predictive models (regression, some on ML). For the medical project, the main thing is to understand the input data: in what format they are (Excel/CSV) and how many observations and features there are approximately? This determines which forecasting model will actually work here, rather than just looking good. I am ready to take a look at your data and provide specifics.

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  • Rating 702

Budget: 6000 UAH Deadline: 7 days

Hello. The category "Databases and SQL" is not entirely accurate. SQL is suitable only for data extraction, while correlations and mathematical models fall under the realm of Data Science and medical statistics.

I am ready to implement both stages of your project in Python (Pandas, SciPy, Scikit-learn) or R:

Statistical analysis: I will perform data cleaning, calculate descriptive statistics, and find correlations (Pearson/Spearman) with mandatory assessment of statistical significance (p-value).

Predictive model: I will build an ML model (for example, logistic regression, Random Forest, or XGBoost) for classification and risk assessment of developing pathologies based on input factors.

Validation: I will evaluate the model's accuracy using ROC-AUC, Precision, and Recall metrics to ensure it has real clinical and predictive value, rather than just being overfitted to the test data.

  • Projects 6
  • Rating 3.9
  • Rating 788

Budget: 8000 UAH Deadline: 10 days

Christina, I see that you need not just a report with correlations, but to transform the accumulated medical data into a predictive tool. I understand that for modeling accuracy, it is important to first properly structure the data arrays and filter out the noise that may affect the results.

I suggest starting with an analysis of the current database structure and data cleansing, after which I will calculate the correlations and test several algorithms for the mathematical model to choose the one that gives the least error on your data. You will receive the final results with a description of the significance of each indicator.

What is the volume of historical data currently available in the database, and is there any labeling regarding how the pathologies developed in specific cases?

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  • Rating 447

Budget: 5000 UAH Deadline: 10 days

Hello, Kristina! My name is Sergey — a data analyst in Python with experience in statistical analysis and building predictive models.

The task is divided into two different stages in terms of volume, so I will honestly separate them:

Stage 1 — statistics and correlations:
• Data cleaning and preparation (missing values, outliers, types)
• Descriptive statistics for all indicators
• Correlation analysis (Pearson / Spearman — depending on the type of data) with significance assessment (p-value), not just "coefficient"
• Visualization and clear conclusions

  • Projects 11
  • Rating 5.0
  • Rating 1 788

Budget: 25000 UAH Deadline: 14 days

Good day! We have experience in processing medical data and building predictive models. We will implement the task using Python (Pandas, Scipy) for statistical analysis and will build a pathology prediction model based on machine learning libraries. We will ensure high accuracy of calculations and correct interpretation of results. We are ready to discuss the implementation details.
25000
14

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  • Rating -
  • Rating 898

Budget: 1000 UAH Deadline: 1 day

Good day, Kristina.

Medical data almost always has gaps and uneven distribution — therefore, the first step will be an audit of the data quality in your database, so that the correlations and forecasting model are based on a reliable foundation rather than on artifacts of incomplete records. Your data will undergo cleaning and normalization through direct SQL queries to PostgreSQL or MySQL, ensuring speed even with large volumes of data without the need for intermediate exports.

After cleaning, you will receive a complete correlation analysis with visualization — this will reveal hidden connections between factors and pathologies. The predictive model is built using AI approaches for classification and regression: each patient will be assigned a quantitative risk assessment for developing pathologies. The accuracy of the model is evaluated using sensitivity and specificity metrics — critically important for medical tasks, where false positives and false negatives have different weights.

The results are presented in a convenient format — Excel, CSV, or JSON — for direct integration into your clinical practice. To ensure the model is adequate, it is advisable to agree on the list of target pathologies and the minimum acceptable level of accuracy before starting work.

Options:

  • Projects 67
  • Rating 5.0
  • Rating 12 691

Budget: 1000 UAH Deadline: 1 day

Hello! I will complete your task quickly and efficiently.

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  • Projects 42
  • Rating 5.0
  • Rating 3 127

Budget: 700 UAH Deadline: 1 day

Good day!

I am a 3 in 1 - doctor, programmer, graduate student. Let's discuss the details of the available data privately, and I will think about how to best accomplish your task.

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  • Rating 327

Budget: 700 UAH Deadline: 3 days

Good day!
I am ready to take on the calculation of statistics for your medical project, including correlation analysis — I work in Excel, and I can accurately calculate and visualize correlations.
Regarding the mathematical model for predicting the development of pathologies — this is a separate, more complex task. I suggest we first discuss what data you have (volume, format, variables) so that I can properly assess the approach and timeline for this part.
Price: 400 UAH for the calculation of statistics with correlations (provided that the data is available in a convenient format)
Deadline: 2–3 days from the moment of receiving the data
I am a newcomer to the marketplace, so I consciously keep the price minimal — the main thing for me now is to work on my first real case and receive honest feedback about our collaboration. I would appreciate the opportunity to demonstrate this in practice.
I am ready to discuss the details and start immediately after agreement.

  • Projects 18
  • Rating 5.0
  • Rating 756

Budget: 1500 UAH Deadline: 2 days

Good day! A university lecturer will complete your project on statistics quickly and efficiently! If you look at my reviews, you will see that I work in SPSS for processing results from statistics and their correlation, and I will build all the graphs! I will be happy to help you!)

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  • Rating -
  • Rating 816

Budget: 11111 UAH Deadline: 11 days

Hello.

I am ready to take on the task. I have extensive experience in processing, analyzing, and structuring complex data sets in Python. For forecasting, I will use modern machine learning algorithms that will accurately identify risks.

The exact cost and timeline will depend on the volume of your data and its cleanliness. I am always available and guarantee clear communication. Please send a sample table for a final assessment!

  • Projects 22
  • Rating 5.0
  • Rating 5 076

Budget: 25000 UAH Deadline: 15 days

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  • Rating 196

Budget: 27000 UAH Deadline: 21 days

We already have a practically ready solution for medical analytics and predictive models, which can be quickly adapted to your data and launch the first working result.

In terms of timing, I would estimate 2-3 weeks for the first version - statistics, correlations, data quality checks, a basic predictive model, and a clear report for the medical team.

Look, there’s a nuance here - for medical forecasting, it’s important not just to calculate correlations, but to check for data bias, missing values, clinical logic of features, and the quality of predictions on a holdout sample.

We can do this as a careful stage - first, data analysis and mathematical modeling, then if needed, add a dashboard or automatic calculations for new patients.

Let me clarify two things.

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