While ML models are powerful tools for predicting diabetes, their lack of interpretability presents a major challenge for clinical adoption. Healthcare professionals require AI models to not only be ...
Using a real-world, nationwide electronic health record–derived deidentified database of 38,048 patients with advanced NSCLC, we trained binary prediction algorithms to predict likelihood of 12-month ...
Ironically, AI, often criticized for exacerbating digital deception and misinformation, holds immense potential to improve ...
As nuclear energy ramps up to move towards decarbonization goals, machine learning and AI techniques offer potential to speed up new reactor design and improve safety of the existing fleet. However, ...
Tech Xplore on MSN8d
Explainable AI can enhance deepfake detection transparencyA new study by SRH University emphasizes the benefits of explainable AI systems for the reliable and transparent detection of ...
More information: Parastoo Semnani et al, A Machine Learning and Explainable AI Framework Tailored for Unbalanced Experimental Catalyst Discovery, The Journal of Physical Chemistry C (2024).
By integrating innovative observability frameworks and automation, his approach enhances model reliability, scalability, and ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback