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Content provided by Rad Chat, Naman Julka-Anderson, and Jo McNamara. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Rad Chat, Naman Julka-Anderson, and Jo McNamara or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.
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E164: Dr. James Lam - novel machine learning algorithm to identify new cancer drug targets

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Manage episode 478431659 series 3011641
Content provided by Rad Chat, Naman Julka-Anderson, and Jo McNamara. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Rad Chat, Naman Julka-Anderson, and Jo McNamara or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

Trigger Warning: This episode discusses cancer.

​​

​​Episode 164: Part of the workforce and education series (part 56).

Description: In this educational episode, Naman Julka-Anderson and Jo McNamara sit down with Dr. James Lam talking about his career as a medical oncologist and work around developing a novel machine learning algorithm to identify new cancer drug targets.

​​

​​James studied Medicine at Cambridge and completed his MBBS at UCL, qualifying in 2017 with Distinction. He holds an MA(Cantab) for research in retinal neuroscience and was ranked first among all UK Medical Oncology ST3 applicants in 2021.

​​Awarded an NIHR Academic Clinical Fellowship, he has contributed to practice-changing oncology trials and cancer cachexia research with the TRACERx Consortium. Now at BioCorteX, he applies computational metagenomics and AI to shaping future cancer care.

​​James remains dedicated to oncology research, with a strong interest in nutrition, fitness, and health optimisation.

​​

​​CPD Reflection Points:

  1. ​​Read through the three publications attached to show notes and reflect upon how this research may impact on clinical practice. ​​

​​Complete this form for your accredited digital badge: Digital Badge Form.

​​

​​Links from the Episode:

​​Research links from the Episode:

​​Rad Chat Links:

​​Credits: Music and jingle credits: Dr. Ben Potts and Adam Cooke.

  continue reading

354 episodes

Artwork
iconShare
 
Manage episode 478431659 series 3011641
Content provided by Rad Chat, Naman Julka-Anderson, and Jo McNamara. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Rad Chat, Naman Julka-Anderson, and Jo McNamara or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

Trigger Warning: This episode discusses cancer.

​​

​​Episode 164: Part of the workforce and education series (part 56).

Description: In this educational episode, Naman Julka-Anderson and Jo McNamara sit down with Dr. James Lam talking about his career as a medical oncologist and work around developing a novel machine learning algorithm to identify new cancer drug targets.

​​

​​James studied Medicine at Cambridge and completed his MBBS at UCL, qualifying in 2017 with Distinction. He holds an MA(Cantab) for research in retinal neuroscience and was ranked first among all UK Medical Oncology ST3 applicants in 2021.

​​Awarded an NIHR Academic Clinical Fellowship, he has contributed to practice-changing oncology trials and cancer cachexia research with the TRACERx Consortium. Now at BioCorteX, he applies computational metagenomics and AI to shaping future cancer care.

​​James remains dedicated to oncology research, with a strong interest in nutrition, fitness, and health optimisation.

​​

​​CPD Reflection Points:

  1. ​​Read through the three publications attached to show notes and reflect upon how this research may impact on clinical practice. ​​

​​Complete this form for your accredited digital badge: Digital Badge Form.

​​

​​Links from the Episode:

​​Research links from the Episode:

​​Rad Chat Links:

​​Credits: Music and jingle credits: Dr. Ben Potts and Adam Cooke.

  continue reading

354 episodes

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