Elisa Rauseo

Consultant Cardiologist & Senior Clinical Lecturer @QMUL @NHSBartsHealth. Cardiovascular imaging. AI. Digital Twins

[Karan Singhal @thekaransinghal]

https://t.co/sbZncI4gF9

[Steffen Petersen @s_e_petersen]

Delighted my team has been recognised in this year’s research excellence award @QMUL using @uk_biobank as a resource. #CVImaging #WHYCMR @EACVIPresident

[Elisa Rauseo @elrauseo]

Great to join today the US Market Access event hosted by SEHTA, MentorOhio, and the London Institute for Healthcare Engineering (LIHE).
Inspiring conversations & global collaboration in digital health!
#DigitalHealth #AIinHealthcare #Cardiology #MedTech

[Dr. Monika Sonu I Founder Healthinnovationtoolbox @sonu_monika]

As shared by Andreas Horn -> Head of AIOps @IBM (LinkedIn)

𝗧𝗵𝗶𝘀 𝗶𝘀 𝗵𝗮𝗻𝗱𝘀-𝗱𝗼𝘄𝗻 𝘁𝗵𝗲 𝗕𝗘𝗦𝗧 𝗮𝗻𝗱 𝗦𝗜𝗠𝗣𝗟𝗘𝗦𝗧 𝗲𝘅𝗽𝗹𝗮𝗻𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝗱𝗮𝘁𝗮 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀 𝘆𝗼𝘂'𝗹𝗹 𝗲𝘃𝗲𝗿 𝘀𝗲𝗲! ⬇️

In today’s AI-driven world, robust data pipelines aren't just a necessity — they're the FUEL that powers everything. ⛽ Without them, AI is just a fancy idea with no real impact.

Data pipelines are the backbone of modern data-driven businesses. And they automate the process of collecting, organizing, and transforming data.

...𝗕𝘂𝘁 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮𝗻 𝗲𝗳𝗳𝗲𝗰𝘁𝗶𝘃𝗲 𝗱𝗮𝘁𝗮 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗶𝘀 𝗾𝘂𝗶𝘁𝗲 𝗵𝗮𝗿𝗱!

Here are the key stages to consider:

1️⃣ 𝗗𝗮𝘁𝗮 𝗦𝗼𝘂𝗿𝗰𝗲𝘀: Collect raw data from various sources.
2️⃣ 𝗗𝗮𝘁𝗮 𝗟𝗼𝗮𝗱𝗲𝗿𝘀: Ingesting the right and trusted data.
3️⃣ 𝗗𝗮𝘁𝗮 𝗟𝗮𝗸𝗲: Store the raw data in a highly accessible format.
4️⃣ 𝗣𝗿𝗲𝗽𝗮𝗿𝗮𝘁𝗶𝗼𝗻/𝗖𝗼𝗺𝗽𝘂𝘁𝗮𝘁𝗶𝗼𝗻: Process and transform the data.
5️⃣ 𝗗𝗮𝘁𝗮 𝗪𝗮𝗿𝗲𝗵𝗼𝘂𝘀𝗲: Store the processed data for specific purposes.
6️⃣ 𝗗𝗮����𝗮 𝗦𝗵𝗮𝗿𝗶𝗻𝗴: Make the data available for analysis and decision-making.

#AI #GenAI #ResponsibleAI #startup #technology #ArtificialIntelligence #automation #chatgpt4 #OpenAIChatGPT #data #healthtech #IoT #technology #5G #telehealth #digitalhealth #mhealth #startups #OpenAI #HealthIT #ChatGPT账号 #WearableTech #DataScience #AI #MachineLearning #dataprotection #DataPrivacy #databreach

@danfiehn @bimedotcom @chidambara09 @RLDI_Lamy @JagersbergKnut @BetaMoroney
@EstelaMandela @GlenGilmore @CurieuxExplorer
@enilev @ArchimedesInte2 @mikeflache @anand_narang @Nicochan33 @IanLJones98
@AlbertoEMachado @FrRonconi @SKodineya
@rafael52987 @KanezaDiane @enricomolinari
@jeancayeux @healthinovatio1 @sonu_monika
@Eli_Krumova @HITLabs10000 @Analytics_699
@SiddharthKS @sulefati7 @devaang @theomitsa
@segundoatdell @bamitav @DigitalMachina

[BSCMR @BSCMR]

AI 🤖 analysis for Biobank CMR🧲 scans show high quality. @DrSuchi_C @elrauseo @s_e_petersen
🔗 https://t.co/hKcT0fkmGV
BSCMR president @SaulMyerson

[Elisa Rauseo @elrauseo]

@hafiz_naderi @BIHSociety @munroe_patsy @Ju_Ra_Ga @s_e_petersen @QMULWHRI @imperialcollege @TheBHF @NIHRresearch Congratulations @hafiz_naderi 👏

[Caroline Roney @CarolineRoney]

Check out the latest feature in The Economist on digital twins to see how our research is bringing personalised healthcare to the clinic! @EDITH_CSA_EU @LiesbetGeris @LauraBevis77 @elrauseo @s_e_petersen @DERI_QMUL @QMULSciEng

[Elisa Rauseo @elrauseo]

@QMULWHRI @s_e_petersen @QMUL @QMULBartsTheLon Many congratulations @s_e_petersen

[Caroline Roney @CarolineRoney]

Incredibly excited about @escardio #ESCCongress2024 tomorrow! Check out @PCM_QMUL presentations across a range of computational modelling, machine learning, and signal processing applications! @ovais19495912 @SemharMisghina @elrauseo @LauraBevis77 @NayAungMD @s_e_petersen

[BSCMR @BSCMR]

Myocardial strain 🧲 predicts cardio-vascular morbidity and death.
@s_e_petersen @elrauseo @DrSuchi_C @kfungkk

[Elisa Rauseo @elrauseo]

@CarolineRoney @EDITH_CSA_EU @LauraBevis77 @DERI_QMUL @QMULSEMS @QMULWHRI It's amazing to be part of this fantastic community and the @CarolineRoney team advancing digital twins in healthcare!

[Emily Lau, MD, MPH @emilyswlau]

Can deep learning derived echocardiogram measures predict cardiovascular outcomes?

Our latest in @JACCJournals

Link 👉https://t.co/D7A3lodOCw

Co-led with @paolodkl @broad_ml4h @broadinstitute @MGHHeartHealth @gpbatra @steven_lubitz @JenHoCardiology

[Caroline Roney @CarolineRoney]

Join us at @RoySocMed on Friday to find out more about digital twins in personalised medicine!
Digital twins: Tailoring medicine insilico
https://t.co/qEhnp4j09h
@RogerHighfield @profandreatn @sairaghafur @PVCoveney

[Selçuk Korkmaz @selcukorkmaz]

Understanding Factor Analysis📊

1/ Introduction:
Factor Analysis is like a detective tool for researchers. Imagine you have a huge pile of data, and you suspect there are hidden patterns or themes. Factor Analysis helps you uncover these hidden themes!

2/ Why use it?:
When you have tons of data, it can be overwhelming. Factor Analysis simplifies things by grouping similar data together. It's like sorting a mixed bag of candies into their respective flavors.

3/ Basic Idea:
Think of Factor Analysis as a librarian. If you give her a stack of books, she'll sort them into categories based on their topics. In the same way, Factor Analysis groups your data based on underlying patterns.

4/ Factors vs Variables:
In our data, we have things we can measure directly, called "variables" (like height, weight, or test scores). But sometimes, there are hidden forces or "factors" (like health or intelligence) that influence these variables. Factor Analysis helps us find these hidden factors.

5/ Reduction:
One of the coolest things about Factor Analysis is its ability to reduce data. Instead of juggling 50 different pieces of data, it might tell you that most of them are influenced by just 3 or 4 main themes or factors.

6/ How does it work?:
Factor Analysis looks at how data points move together. If two variables (like time spent studying and test scores) often rise and fall together, they might be influenced by a common factor (like motivation).

7/ Visualization:
Imagine plotting all your data on a giant chart. Factor Analysis draws lines (or axes) that best capture the patterns in the data. These lines represent our hidden factors.

8/ Not a crystal ball:
While Factor Analysis is powerful, it doesn't "prove" anything. It suggests possible hidden factors, but it's up to researchers to interpret and validate them.

9/ Types of Factor Analysis:
Exploratory Factor Analysis (EFA): When you're not sure what you're looking for and want to explore.
Confirmatory Factor Analysis (CFA): When you have a hunch about the hidden factors and want to test your theory.

10/ Steps in Factor Analysis (oversimplified):
Collect Data: Get as much relevant data as you can.
Choose the Method: Decide on EFA or CFA based on your goals.
Run the Analysis: Use statistical software to crunch the numbers.
Interpret the Results: Identify the hidden factors and see how they relate to your data.
Validate: Check if your findings make sense and if they can be replicated.

11/ Real-world Applications:
From psychology (understanding personality traits) to finance (identifying investment themes), Factor Analysis is used in various fields to make sense of complex data.

12/ Conclusion:
Factor Analysis is like a magnifying glass for data. It doesn't give all the answers but reveals patterns and themes that can guide further research. It's a powerful tool for anyone looking to uncover the hidden stories in their data!

#DataScience #Statistics

[Frontiers in Radiology @FrontRadiology]

📢Submit your research to this impactful #ResearchTopic led by our Topic Editors Alun Hughes, Henk JMM Mutsaerts, and Topic Coordinator Elisa Rauseo @elrauseo!

👉https://t.co/E0lwmo47Tc
🗓️Submit by 29 September 2023

[Eric Topol @EricTopol]

Very good editorial today on individualized breast cancer screening with #AI in the future @radiology_rsna
https://t.co/A4YmJFEtdu
Concept reviewed
https://t.co/E5dbM4pJFX
and here
https://t.co/ofEBWUMSrZ

[Elisa Rauseo @elrauseo]

@LoukiaKaratzia @BartsHospital @QMULWHRI Congratulations 🎉

[Elisa Rauseo @elrauseo]

@BHFDataScience @s_e_petersen Many congratulations, @s_e_petersen, on this well-deserved achievement 👏

[Elisa Rauseo @elrauseo]

@karimjerbineuro Amazing. That’s the essence of teamworking!

[JACC Journals @JACCJournals]

🆕 issue of #JACCIMG is out!

Large @UK_Biobank imaging study shows links between #IschemicHeartDisease, vascular risk factors, & accelerated brain aging ➡️ increased risk of #dementia. Brain aging to communicate brain health could promote healthier lifestyles https://t.co/7rZV5VtxJN #CardioTwitter