Synopsis of Social media discussions

The discussions primarily highlight the importance of machine learning in predicting heart failure outcomes using easily accessible clinical features like serum creatinine and ejection fraction, with examples such as references to the dataset and praise for the study’s potential for improving medical predictions. The tone varies from supportive technical appreciation to curiosity about practical applications, reflecting both interest and engagement.

A
Agreement
Moderate agreement

Most discussions express support or acknowledgment of the study's findings, indicating general agreement with its significance.

I
Interest
High level of interest

Posts demonstrate high curiosity, often mentioning the innovative use of machine learning for survival predictions, demonstrating keen interest.

E
Engagement
Moderate level of engagement

Some comments delve into details about the dataset and methodology, showing moderate engagement and understanding.

I
Impact
Moderate level of impact

User comments suggest an appreciation for the study's potential influence on healthcare practices, though not all see it as a groundbreaking shift.

Social Mentions

YouTube

2 Videos

Twitter

35 Posts

Blogs

2 Articles

News

16 Articles

Metrics

Video Views

35,610

Total Likes

910

Extended Reach

132,224

Social Features

55

Timeline: Posts about article

Top Social Media Posts

Posts referencing the article

Predicting Heart Failure Survival Using Machine Learning Techniques

Predicting Heart Failure Survival Using Machine Learning Techniques

This video explains how data science and machine learning are used to accurately predict survival in heart failure patients by analyzing serum creatinine and ejection fraction, emphasizing their importance as key risk factors.

April 22, 2023

35,559 views


Machine Learning for Heart Failure Survival Prediction Using Key Biomarkers

Machine Learning for Heart Failure Survival Prediction Using Key Biomarkers

This video discusses how machine learning can effectively predict heart failure patient survival using serum creatinine and ejection fraction, emphasizing their importance as key risk factors in survival models.

October 11, 2021

51 views


  • No more
    @Heart_livingM (Twitter)

    Join the discussion and read the entire study at https://t.co/50MlhLsziD ! How about employing basic signs to make intricate forecasts?
    view full post

    June 25, 2024

  • балканский дата-пёс
    @unemployed_ds (Twitter)

    Вообще, авторы целую статью написали, где они на этих данных построили модель. Я буду в неё загляну по ходу дела. 2/n https://t.co/EE4vJOCTNP
    view full post

    October 31, 2022

  • Al VA
    @alzapress (Twitter)

    #ArtificialIntelligence #Artificial_Intelligence #heartattack #heartfailure #healthcare ML can predict patients’ #survival from their #data and can individuate the most important features among those included in their #Medical #records https://t.co/vchZgs27Pf
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    March 15, 2022

    1

  • İTF Yapay Zeka
    @itfyapayzeka (Twitter)

    Örnek medikal veri işlemesi (Kalp yetmezliği) https://t.co/nQTohw8EC8 Makale; https://t.co/AwYYDIogOU
    view full post

    August 13, 2020

    1

  • The Data Science Bot
    @datasciencebot_ (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    August 11, 2020

    24

  • HubOfML
    @hubofml (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    August 11, 2020

    24

  • La Ouest-africaine
    @west_africaine (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    August 11, 2020

    24

  • Gnuts about Code
    @CodeGnuts (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    August 11, 2020

    24

  • DavideChicco.it
    @DavideChicco_it (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    August 11, 2020

    24

  • Windy
    @HelanDisney (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    July 20, 2020

    24

  • uh-oh
    @qualystat (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    July 19, 2020

    24

  • Gnuts about Code
    @CodeGnuts (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    July 19, 2020

    24

  • Medicine_News
    @Medicine__News (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    July 19, 2020

    24

  • Aaron ''Midlife Coder'' Cuddeback
    @AaronCuddeback (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    July 19, 2020

    24

  • Rajesh
    @imrajeshberwal (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    July 19, 2020

    24

  • Curious Luke
    @TheCuriousLuke (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    July 19, 2020

    24

  • Lane
    @Loiss_Vaku (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    July 19, 2020

    24

  • BOT Kitty
    @BotRaj1 (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    July 19, 2020

    24

  • LinuxDreams
    @LinuxDreams (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    July 19, 2020

    24

  • Code Newbie Bot
    @_codenewbiebot (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    July 19, 2020

    24

  • I'm a Bot #END SARS #SARSMUSTEND
    @End_Sars2020 (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    July 19, 2020

    24

  • The Data Science Bot
    @datasciencebot_ (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    July 19, 2020

    24

  • Inferno
    @theInfernobot (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    July 19, 2020

    24

  • JS Bits
    @js_bits (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    July 19, 2020

    24

  • HubOfML
    @hubofml (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    July 19, 2020

    24

  • Tech Bot
    @TechBot19 (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    July 19, 2020

    24

  • Machine Learning Bot
    @ML_Tweet_Bot (Twitter)

    RT @PoetryAssessor: Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #…
    view full post

    July 19, 2020

    24

  • Poetry Assessor
    @PoetryAssessor (Twitter)

    Machine learning outperforms 'traditional' tests in predicting heart failure survival: https://t.co/iN9eeJOgm5 #Linux #Python #Java #DataScience #100DaysOfCode #Analytics #BigData #MachineLearning #Javascript #Flask #Django #Artscorer #FemTech #WomenWhoCode #Medical #diagnosis
    view full post

    July 19, 2020

    11

    24

  • Giuseppe Jurman
    @Giuseppe_Jurman (Twitter)

    RT @DavideChicco_it: The heart failure clinical record dataset @Giuseppe_Jurman and I used for our "Machine learning can predict survival o…
    view full post

    June 16, 2020

    1

  • DavideChicco.it
    @DavideChicco_it (Twitter)

    The heart failure clinical record dataset @Giuseppe_Jurman and I used for our "Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone" article is now available on the @UCIrvine ML Repository: https://t.co/T15KDeK4p3
    view full post

    June 16, 2020

    4

    1

  • THE AI FUTURE SHOW Podcast #intoAI #AI
    @into_AI (Twitter)

    Machine learning can predict survival of patients with heart failure from serum - https://t.co/kGeW8X3qGF #machinelearning #intoAInews
    view full post

    February 5, 2020

  • Elisa Solano
    @elitayoan (Twitter)

    RT @DavideChicco_it: The new paper "Machine learning can predict survival of patients with heart failure from serum creatinine and ejection…
    view full post

    February 4, 2020

    5

  • Alessia Marcolini
    @viperale (Twitter)

    RT @DavideChicco_it: The new paper "Machine learning can predict survival of patients with heart failure from serum creatinine and ejection…
    view full post

    February 3, 2020

    5

  • Giuseppe Jurman
    @Giuseppe_Jurman (Twitter)

    RT @DavideChicco_it: The new paper "Machine learning can predict survival of patients with heart failure from serum creatinine and ejection…
    view full post

    February 3, 2020

    5

  • DavideChicco.it
    @DavideChicco_it (Twitter)

    The new paper "Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone" that I wrote with @Giuseppe_Jurman (@FBKcom @mpbalab) has been published on @BioMedCentral BMC Medical Informatics!
    view full post

    February 3, 2020

    16

    5

  • s13369 023 08183 Z - Arabian | PDF | Heart Failure | Mathematical ...

    https://doi.org/10.1186/s12911-020-1023-5 doi.org/10.1016/j.ins.2021.11.051 4. Mehedi Zaman, S. M.; Qureshi, W. M.; Raihan, M. M. S.; Bin 20. Doğan, C ...
    view full post

    December 18, 2025

    News

  • Grupo 3 | PDF | Polycystic Ovary Syndrome | Machine Learning

    https://doi.org/10.1186/s12911-020-1023-5. PMID: 32013925; PMCID: PMC6998201. ple trials, it was identified that PSO and FF algorithm with RF classifier
    view full post

    December 18, 2025

    News

  • IJGM 325609 Machine Learning Model Applied On Chest X Ray ...

    doi:10.1186/ Available from: https://www.kaggle.com/paultimothymooney/ s12911-020-1023-5 chestAQ10 xray-pneumonia. Accessed: May 12, 2020. 39. James H ...
    view full post

    December 18, 2025

    News

  • Savedrecs 4 | PDF

    ... 10.1186/s13040-021-00244-z. Chicco D, 2020, BMC MED INFORM DECIS, V20, DOI 10.1186/s12911-020-1023-5. Chicco D, 2019, PLOS ONE, V14, DOI 10.1371/journal.pone ...
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    December 18, 2025

    News

  • 22 Vol 102 No 5 | PDF | Machine Learning | Systematic Review

    10.1186/s12911-020-1023-5. [87] D. Mpanya, T. Celik, E. Klug, and H. Ntsinjana, “Machine learning and statistical methods for predicting mortality in heart ...
    view full post

    December 18, 2025

    News

  • Chicco-Jurman2020 Article MachineLearningCanPredictSurvi | PDF ...

    Chicco and Jurman BMC Medical Informatics and Decision Making (2020) 20:16. https://doi.org/10.1186/s12911-020-1023-5 ...
    view full post

    December 18, 2025

    News

  • Enhancing predictive modelling and interpretability in heart failure ...

    doi: 10.1186/s12911-020-1023-5. [24] M. A-M. Hasan, J. Shin, U. Das, and A. Y. Srizon, “Identifying prognostic features for predicting heart failure by using
    view full post

    December 18, 2025

    News

  • Prognostic Modeling For Heart Failure Survival A Classification ...

    DOI: 10.1186/s12911-020-1023-5. PMID: 32013925; PMCID: Regres- PMC6998201. ... Analysis of Heart Failure Patients: A Case Study,” PLOS ONE, vol. 12, p. e0181001, ...
    view full post

    December 18, 2025

    News

  • Prediction of Deth Event Due To Heart Failure Using Machine ...

    ... 10.1186/s12911-020-1023-5. CPK and serum creatinine are related, my hypothesis is not %100 percent wrong. Variables and model methods are ...
    view full post

    August 10, 2025

    News

  • PyTorch Introduction - Enter NonLinear Functions | Towards Data ...

    ... 10.1186/s12911-020-1023-5#Sec2]. Written By. Ivo Bernardo. See all from Ivo Bernardo · Artificial Intelligence, Deep Learning, Machine Learning ...
    view full post

    January 12, 2024

    Blogs

  • Pytorch Introduction — Enter NonLinear Functions | by Ivo Bernardo ...

    ... under licence Creative Commons https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-020-1023-5#Sec2]. 174. Pytorch.
    view full post

    January 11, 2024

    News

  • Heart Disease Prediction with ML Techniques | PDF | Machine ...

    m/articles/10.1186/s12911-020-1023-5 16. "Machine Learning and Deep Learning for Heart Disease Diagnosis: A Review" https://www.future ...
    view full post

    October 6, 2023

    News

  • Detecting Heart Failure using Machine Learning (Part 1) | by ...

    ... %20with%20enough%20force. 2) https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-020-1023-5. 5. Data Science · Machine ...
    view full post

    March 22, 2021

    News

  • Finding Important Features using Genetic Algorithms | by Peijin ...

    https://doi.org/10.1186/s12911-020-1023-5. This data set has 12 features and you can download it from the UCI Machine Learning Repository. It ...
    view full post

    November 5, 2020

    News

  • Machine Learning Mini-Project 4: Finding Important Features using ...

    https://doi.org/10.1186/s12911-020-1023-5. This data set has 12 features and you can download it from the UCI Machine Learning Repository. It ...
    view full post

    November 5, 2020

    Blogs

  • Predicting Heart Failure Using Machine Learning, Part 1 | by Andrew ...

    https://doi.org/10.1186/s12911-020-1023-5. The above table describes the features of clinical and laboratory data provided in the dataset ...
    view full post

    September 26, 2020

    News

  • 机器学习还能预测心血管疾病?没错,我用Python写出来了_数据

    biomedcentral.com/articles/10.1186/s12911-020-1023-5#Abs1. 平台声明. 评论. 全部. 还没有人评论过,快来抢首评. 写评论. 微信好友; 朋友圈; QQ ...
    view full post

    September 14, 2020

    News

  • Pytorch: Linear Regression Model to predict life tendency of people ...

    https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-020-1023-5. 2- Introduction to PyTorch. Before moving to the analysis ...
    view full post

    June 21, 2020

    News

Abstract Synopsis

  • Machine learning can effectively predict the survival of heart failure patients using only serum creatinine and ejection fraction, highlighting these as key risk factors.
  • The study compares traditional biostatistics and machine learning methods for feature ranking, both identifying serum creatinine and ejection fraction as the most important predictors.
  • Models utilizing just these two features outperform those using the full dataset, confirming their sufficiency and importance in accurate survival predictions.]