biomedical urjc

Biomedical engineering - Deep Learning @ETSIT_URJC Óscar Barquero-Pérez @obarquero, @miguelkr92, @my_phd_life, @rebe_goya

[biomedical urjc @BiomedicalUrjc]

Non-invasive estimation of atrial fibrillation driver position using l... https://t.co/DdBX02MFvW

[biomedical urjc @BiomedicalUrjc]

https://t.co/N0FxuW53Vl

[biomedical urjc @BiomedicalUrjc]

Near infrared spectroscopy (NIRS) and machine learning as a promising ... https://t.co/E9chbEEJ7r

[biomedical urjc @BiomedicalUrjc]

https://t.co/6WUyAO7l0I

[Andreu M. Climent @amcliment]

🧵Muy decepcionado con @ANECAinfo y @UniversidadGob su desincentivo hacia la #multidisciplinariedad en la ciencia. Queremos avanzar, pero ¿cómo hacerlo si nos constriñen a áreas del conocimiento? El futuro está en las fronteras entre conocimientos. Dentro hilo enfadado:

[Anna Clemens, PhD @scientistswrite]

As an academic writing coach, here are the 5 most common mistakes I see researchers make when they write their Discussion sections.

A thread. 🧵

#PIchat #newPI #ECRchat

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Mistake #1: Providing paragraphs of background information

📝 The Introduction section is meant for context. In the Discussion section, any mentioned background info needs to be *discussed* together with your own findings.

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Mistake #2: Expecting the reader to have read all previous sections

💡 Tell the whole story by restating the problem you are solving with your study so that readers understand the motivation for your research.

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Mistake #3: Describing the purpose and result of each experiment

🔬 This should be provided in the Results section. The Discussion is for actually *discussing* your findings, i.e. how your study has changed the state of the art and what the potential implications are.

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Mistake #4: Too general implication statements

🌍 Avoid too broad statements that could mean everything and nothing. Be specific when you describe the potential implication of your findings even when some of them are speculative.

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Mistake #5: Skipping the discussion altogether

🚫 Discussion sections are helpful for fellow researchers, journal editors and also journalists! If you have a combined Results & Discussion section, don't forget to include the discussion part!

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TL;DR: The 5 most common mistakes in the Discussion section:

#1: Providing too much background info
#2: Not restating the motivation of your study
#3: Describing the purpose of each experiment
#4: Too general implication statements
#5: Skipping the discussion altogether

[biomedical urjc @BiomedicalUrjc]

La alumna Sara Valiente, premiada por un trabajo que ayuda al tratamiento de las arritmias - Universidad Rey Juan Carlos https://t.co/QQx8wT5RTp

[Corify Care @corifyAF]

Last week, Corify Care technology was used in #HospitalGregorioMarañon and retransmitted for the XIX Ablation and navigation systems course

[Corify Care @corifyAF]

Here, Dr. @atienza_felipe describes how the ACORYS MAPPING SYSTEM was used during a case of paroxysmal AF ablation and mitral stenosis valvuloplasty.

[Brown Neuroscience @BrownUNeuro]

Most grad school applications are due in less than a week! 📝If you're still adding those finishing touches, here are some tips to help you with the application process (1/8):

[Rayleigh Lord | Javier González Monge @RayleighLord]

Este archivo de configuración fija muchos parámetros de la figura una vez invocado.

Aquí os dejo el estilo que he usado yo para publicaciones científicas y que creo que funciona muy bien, aunque se puede retocar cualquier parámetro que consideréis.

https://t.co/Ww4DNlNJBo

[biomedical urjc @BiomedicalUrjc]

2o premio en la competición de estudiantes de GIB @caseib2022 @saravalij @urjc @ETSIT_URJC: gran trabajo

[CASEIB 2022 @CASEIB2022]

Sesión de premios FENIN-SEIB para estudiantes de grado en ingeniería biomédica. El nivel de las presentaciones ha sido altísimo. Muchas gracias a todos los candidatos. #CASEIB2022 #XL #XLPerformance

[biomedical urjc @BiomedicalUrjc]

Bien trabajo Sara

[biomedical urjc @BiomedicalUrjc]

@saravalij is about to represent @urjc @ETSIT_URJC in the student competition at @CASEIB2022

[Avi Kumar Talaviya @avikumart_]

Kaggle is a fundamentally powerful platform to learn data science🤖🚀

Here are the TOP 7 kaggle resources to learn data science and
solve complex data problems (Don't miss it!)

🧵👇

[Mark Tenenholtz @marktenenholtz]

You should always work on improving your model evaluation skills.

Model evaluation is the worst taught skill in machine learning, and I believe the best way of improving is through practice.

But, this paper from @rasbt is by far my favorite single written resource:

[Dr Asma Jabeen @DrasmaJabeen1]

How to write scientific article? Step by step guide for beginners #phd #research #researcher #AcademicTwitter https://t.co/RnTF9xHid2

[biomedical urjc @BiomedicalUrjc]

@saravalij representará a la @urjc @ETSIT_URJC en la competición de estudiantes @CASEIB2022: Localización de Drivers en Fibrilación Auricular con Redes Convolucionales LSTM. Buen trabajo. En 2020 y 2022 alumnos de nuestro grupo han representado a la @urjc. Seguimos!

[Rosana Ferrero 📈📊🙌 @RosanaFerrero]

🤩10 reglas o consejos para escribir y estructurar un artículo científico
👥 Mensh y Kording (2017)
🔗 https://t.co/i8m90cqdj1

#datascience #analytics #science #papers #publish #dataviz