Moein Shariatnia
Moein Shariatnia
Contributor, The Yuan

Moein Shariatnia is a machine learning developer and medical student. He develops computer vision and NLP applications in healthcare and beyond using deep learning models. His research focus is the transfer of learning and generalization of ML models.

A case study of failure shows the difficulty of adopting AI in healthcare
Success stories abound about the adoption of AI in healthcare and other domains, yet failures may prove even more instructive as governments, companies, and persons seek to navigate the age of AI. AI and ML expert Moein Shariatnia shines the spotlight on one such cautionary tale.
Moein Shariatnia  |  Jan 23, 2024
The Digital Visionary - with Moein Shariatnia and David Wood
In this episode, we discuss AI models reshaping diabetic retinopathy diagnosis and management, addressing challenges with enhanced accuracy. Real-world studies validate their effectiveness, often outperforming manual grading. Tune in to listen why the convergence of medical and machine learning expertise becomes increasingly crucial for future healthcare professionals.
Delta Dialog  |  Dec 07, 2023
AI-driven Healthcare - with Moein Shariatnia and David Wood
The dynamic landscape of AI in healthcare has witnessed a remarkable shift from single-task models to the emergence of powerful multimodal deep learning models. Tune in as we navigate the intersection of technology and healthcare, highlighting both the promises and pitfalls in the journey toward a more efficient and patient-centric medical future.
Delta Dialog  |  Nov 23, 2023
Medical field takes first steps toward tackling ‘hallucination’ by LLMs
Domain knowledge
‘Hallucination,’ which refers to LLMs and other AIs presenting falsehoods as seemingly plausible facts, is a grave problem and one yet to be resolved. This becomes especially urgent when patients’ lives are at stake, although hope is at hand, writes ML developer Moein Shariatnia.
Moein Shariatnia  |  Nov 10, 2023
Novel biomarker discovery opens a window into learning from DL models
Deep learning models have made great strides since the time when all data samples had to be labeled with ground truths and input manually for such models to execute tasks. They now offer ever greater capabilities and reliability of prognoses and thus much instruction for experts.
Moein Shariatnia  |  Aug 01, 2023
AI healthcare research is prone to numerous flaws, pitfalls
Domain knowledge
The ever swifter, wider use of AI in healthcare research makes for many mistakes along the way and often yields inherently flawed research, explains ML developer and medical student Moein Shariatnia, who devises computer vision and NLP applications in healthcare with DL models.
Moein Shariatnia  |  Jun 09, 2023
Multi-modality AI in medicine
Unlike most AI, which focuses on and is trained for handling just one specific modality, multimodal AI models can handle different modalities such as image, text, and speech at the same time, in addition to narrow and specific tasks. This means that, if and when multi-modality AI progresses to the point where it can deploy on a vast scale, it will truly revolutionize medicine and many other fields.
Moein Shariatnia  |  Mar 28, 2023
Deep generative models deploy in radiology
New era
Generative models are hot items in tech news today. Stable Diffusion and Midjourney - which create amazing artwork - and ChatGPT, which writes excellent essays for an input prompt - have astounded many. Similar models are also in the works for healthcare - especially for radiology - to address their real-world challenges. ML developer and medical student Moein Shariatnia sketches a brief history of deep generative models and explains how they work and their use in medical imaging.
Moein Shariatnia  |  Jan 31, 2023
Google’s AI will help the world by detecting diabetic retinopathy
Google has some of the most formidable AI capabilities in the world, though among their applications diabetic retinopathy is not the first that springs to mind. As diabetics are likelier to develop eye-related disorders and their numbers continue to grow worldwide, this is extremely valuable.
Moein Shariatnia  |  Nov 26, 2022