DEV Community: Francisco Maria Calisto

Celebrating 100 Days of Continuous GitHub Contributions

Francisco Maria Calisto — Tue, 09 Jul 2024 20:38:59 +0000

Hey everyone!

I’m excited to share that I’ve just hit 100 days of continuous contributions from my GitHub profile (@FMCalisto). It’s been an incredible journey, filled with learning, challenges, and a lot of coding. I wanted to take a moment to reflect on this milestone and share some insights with you all.

How It All Started

This streak began on April 1st. No, it wasn’t an April Fool’s joke! I decided to push myself to contribute to GitHub every single day. Initially, it was a way to sharpen my skills and stay disciplined, but it quickly became much more than that. It turned into a daily ritual that I looked forward to, a way to engage with the community, and a personal challenge to see how far I could go.

My Daily Routine

To keep the streak alive, I developed a daily routine:

Morning Planning: I’d kick off each day with a quick planning session to decide what I’d work on.
Consistent Coding: Whether it was a busy workday or the weekend, I dedicated at least an hour to coding.
Leveraging Tools: Tools like VS Code and GitHub Desktop were my best friends, helping streamline my workflow.
Taking Breaks: To avoid burnout, I made sure to step away from the screen and take breaks.

Highlights of My Contributions

Over these 100 days, I had the chance to work on a variety of initiatives:

MIMBCD-UI: Added some cool new tools for medical imaging data curation in Machine Learning (ML) projects.
MIDA: Published the LaTeX source of my PhD Thesis and some other research documents.

The Challenges

It wasn’t always smooth sailing:

Time Management: Balancing my contributions with other responsibilities was tough. Prioritizing and managing my time effectively was key.
Staying Motivated: There were days when it was hard to stay motivated. Focusing on the impact of my work and the support from the community kept me going.
Avoiding Burnout: Ensuring I took breaks and practiced self-care helped me maintain my energy and enthusiasm.

Lessons Learned

This journey taught me a lot:

Consistency Pays Off: Small, daily efforts can lead to big achievements.
Community is Everything: The support and feedback from the developer community are invaluable.
Never Stop Learning: Every contribution is an opportunity to learn and grow.

Looking Ahead

So, what’s next?

New Initiatives: I’m planning to start some new open-source projects and would love for you to join me.
Sharing Knowledge: I’ll keep writing posts and tutorials to share what I’ve learned.
Making an Impact: I aim to contribute to projects that can make a real difference in the community.

Wrapping Up

Hitting 100 days of continuous contributions is something I’m really proud of. It’s been a journey of growth, learning, and connecting with others. I hope my experience inspires you to start your own streak or just keep contributing in your own way.

Thanks for reading and being part of this journey. Let’s keep coding and making awesome things together!

Feel free to drop your questions and thoughts in the comments below. I’d love to hear about your experiences and any tips you have for maintaining a contribution streak.

Answer: Find Similarity on Excel Column - Brand, Product Name and Weight

Francisco Maria Calisto — Mon, 13 Mar 2023 10:36:04 +0000

Mar 13 '23

For that, you can use an NLP library, such as spaCy or NLTK to tekenize the product names and compute their similarity scores. This is done by iterating over all the products in both datasets and computing the similarity scores between each pair of products. Additionally, it will be setting…

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What is the difference between a CornerstoneJS viewport and an image object?

Francisco Maria Calisto — Mon, 06 Mar 2023 12:36:19 +0000

Mar 6 '23 Comments: 1 Answers: 0

CornerstoneJS is a JavaScript library for displaying medical images in web browsers. We are using this tool within our Deep Learning (DL) projects, and have some specific questions. The CornerstoneJS documentation does not provide a clear relationship between the viewports and the image object.

In addition, the viewports can be…

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Answer: How to make list of cars into string?

Francisco Maria Calisto — Thu, 05 Jan 2023 12:41:30 +0000

Jan 5 '23

You can try the following:

def car_list_as_string(cars: list) -> str
    """
    Create a list of cars.
    The order of the elements in the string is the same as in the list.

    [['Audi', ['A4']], ['Skoda', ['Superb']]] =>
    "Audi A4,Skoda Superb"
    """
    car_strings = []
    for car in cars:
        brand = car[0]

…

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Answer: Error: Warning: Middleware for RTK-Query API at reducerPath "api" has not been added to the store

Francisco Maria Calisto — Thu, 05 Jan 2023 12:21:21 +0000

Jan 5 '23

This error is caused by the syncMiddleware middleware that is being added to the Redux store. It appears that this middleware is not implemented correctly, as it is not returning the result of calling next(action) for action. To fix this error, you should modify the syncMiddleware middleware to correctly pass…

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Answer: RLlib: Collecting metrics for different variation of the same experiment

Francisco Maria Calisto — Tue, 03 Jan 2023 16:17:22 +0000

Jan 3 '23

It sounds like you want to run multiple experiments with different variations of the same environment and collect metrics for each variation. One way to do this with RLlib is to use the tune.run_experiments function, which allows you to specify multiple experiments to run in parallel or sequentially.

To set…

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How to convert duration of MM:SS to seconds in Google Sheets?

Francisco Maria Calisto — Wed, 28 Dec 2022 01:19:08 +0000

Jun 30 '22 Comments: 2 Answers: 5

As duration of a task, suppose that we have a column with cells formatted as MM:SS that would like to convert to seconds. Mathematically speaking, the solution is simple. We just need to compute MM * 60 + SS converting it to seconds. Additionally, we followed this strategy to solve…

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Answer: JavaScript date time conversion not returning the value

Francisco Maria Calisto — Wed, 28 Dec 2022 01:17:46 +0000

Dec 28 '22

You need to call the toLocaleDateString method by adding parentheses after it, like this:

var start = match.startAt
console.log(start);
var startTime = new Date(start);
var t = startTime.toLocaleDateString();

The t variable should be a reference to the toLocaleDateString function, which makes the right approach to do it. However, you need…

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Using Artificial Intelligence in Medical Imaging: A First Step Tutorial with Python Code Examples

Francisco Maria Calisto — Sun, 11 Dec 2022 04:40:00 +0000

Artificial intelligence (AI) has made significant strides in the field of medical imaging, allowing doctors and other medical professionals to better diagnose and treat their patients. One key area where AI has been particularly effective is in the detection and diagnosis of diseases and conditions such as cancer and heart disease. AI algorithms are able to analyze medical images, such as X-rays, MRIs, and CT scans, and identify patterns and abnormalities that may indicate the presence of a particular condition. This can be done much more quickly and accurately than by a human alone [1, 2, 3], allowing doctors to make more informed decisions about their patients' care.

In addition to improving diagnostic accuracy, AI in medical imaging can also help reduce the workload of medical professionals. By automating some of the more routine tasks involved in analyzing medical images, doctors, and other healthcare workers can focus on more important aspects of patient care. Another essential area between both AI and medical imaging fields is Human-Computer Interaction (HCI) to study how we can achieve higher interpretability of the AI outcomes. HCI is a field of study that focuses on how humans interact with computers and other technology. It is a significant aspect of the development of AI systems for medical imaging, as it helps ensure that these systems are easy to use and understand by medical professionals. By designing AI systems with intuitive interfaces and clear instructions, developers can ensure that medical professionals are able to use them effectively and efficiently during their medical practice.

Tutorial

In this tutorial, we will explore how to use AI in medical imaging. By leveraging the power of AI algorithms, medical professionals can improve the accuracy and efficiency of their work. In this article, we will provide Python code examples that show how to use AI algorithms to analyze medical images and make more informed decisions about patient care. We will also discuss the importance of HCI in the development of AI systems for medical imaging.

The code uses the pydicom library to read a DICOM image from a file. DICOM (Digital Imaging and Communications in Medicine) is the standard format for storing and transmitting medical images. It is commonly used in hospitals and other healthcare settings.

The first step in the code is to import the pydicom library:

import pydicom

Next, we use the dcmread() function from the pydicom library to read the DICOM image from a file:

image = pydicom.dcmread('medical_image.dcm')

The dcmread() function takes the file path of the DICOM image as an argument, and returns the image data as a Dataset object. The Dataset object contains the pixel data for the image, as well as metadata about the image, such as its dimensions, resolution, and other information.

Once we have read the DICOM image, we can pass it to the AI algorithm for analysis:

results = AI_algorithm.analyze(image)

The AI algorithm will use its pre-trained model to analyze the image and identify any patterns or abnormalities that may be present. The results of the analysis are returned as a Result object, which contains the findings of the algorithm.

Finally, we print the results of the analysis to the console:

print(results)

This code provides a simple example of how to use an AI algorithm to analyze a DICOM image. In a real-world application, the results of the analysis would be used by medical professionals to make decisions about the patient's care.

Here is the final revised version of the code that uses the pydicom library to read a DICOM image:

import pydicom

# Load the DICOM image
image = pydicom.dcmread('medical_image.dcm')

# Use the AI algorithm to analyze the image
results = AI_algorithm.analyze(image)

# Print the results
print(results)

Acknowledgments

This post is supported by the case studies of MIMBCD-UI, MIDA, and BreastScreening projects at IST from ULisboa. The three projects are strongly sponsored by FCT, a Portuguese public agency that promotes science, technology, and innovation, in all scientific domains. The genesis of this post was a research work between ISR-Lisboa and ITI, both associated laboratories of LARSyS. From these institutions, I would like to convey a special thanks to Professor Jacinto C. Nascimento and Professor Nuno Nunes for advising me during my research work.

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References

[1] Francisco Maria Calisto, Nuno Nunes, Jacinto C. Nascimento, Modeling adoption of intelligent agents in medical imaging, International Journal of Human-Computer Studies, Volume 168, 2022, 102922, ISSN 1071-5819, https://doi.org/10.1016/j.ijhcs.2022.102922

[2] Francisco Maria Calisto, Carlos Santiago, Nuno Nunes, Jacinto C. Nascimento, BreastScreening-AI: Evaluating medical intelligent agents for human-AI interactions, Artificial Intelligence in Medicine, Volume 127, 2022, 102285, ISSN 0933-3657, https://doi.org/10.1016/j.artmed.2022.102285

[3] Francisco Maria Calisto, Carlos Santiago, Nuno Nunes, Jacinto C. Nascimento, Introduction of human-centric AI assistant to aid radiologists for multimodal breast image classification, International Journal of Human-Computer Studies, Volume 150, 2021, 102607, ISSN 1071-5819, https://doi.org/10.1016/j.ijhcs.2021.102607

Finding the maximum integer value contained in a matrix using Java

Francisco Maria Calisto — Sat, 16 Jul 2022 19:33:32 +0000

Jun 3 '15 Comments: 4 Answers: 3

-1

To find the maximum integer value in a matrix I try to code some of that:

/*
 * @param ints
 * @return the max value in the array of chars
 */

public static int maxMatrix(int [][] ints) {
    int max = ints[0][0];

    for(int i = 0; i < ints.length; i++)

…

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Efficiency of Multithreaded Loops

Francisco Maria Calisto — Thu, 04 Nov 2021 10:51:25 +0000

Jan 27 '15 Comments: 3 Answers: 1

Greetings noble community,

I want to have the following loop:

for(i = 0; i < MAX; i++)
    A[i] = B[i] + C[i];

This will run in parallel on a shared-memory quad-core computer using threads. The two alternatives below are being considered for the code to be executed by these threads…

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How to create a script to add, commit and push file by file a set of new or changed files?

Francisco Maria Calisto — Tue, 26 Oct 2021 09:48:01 +0000

Oct 26 '21 Comments: 3 Answers: 0

I want to create a shell script that add, commit and push new or changed files to a repository. Currently, my script is doing this by iterating file by file, which takes too much time. My requirement is to still doing this file by file, but this time I…

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