How a healthy lifestyle is associated with longevity, less cardiovascular and cancer-related mortality: A plasma metabolic signature of lipid pathways assessed in 4 US cohorts with 28-year follow-up accounts for ~50% https://
cell.com/med/fulltext/S
2666-6340(24)00040-0
… @ajtessierRD @MartaGuasch1
DATA
-
Plasma metabolic signature predicts longevity cardiovascular cancer mortality
By
–
-
SAS HBCU+ Fellows Shape Future of Analytics Education
By
–
Meet our 2024 SAS HBCU+ Fellows! These 4 educators from Virginia State University @VSU_1882
, Dillard University @du1869
, North Carolina Central University @NCCU and North Carolina A&T State University @ncatsuaggies are shaping the future of analytics. http://
2.sas.com/6014Vvw98 -
Identifying AI Bias Causes in Medical Imaging Applications
By
–
It's one thing to identify bias of an #AI in medicine. It's another to identify its cause.
As nicely demonstrated here with imaging https://
nature.com/articles/s4225
6-024-00797-8
… @NatMachIntell @GlockerBen @c_jones_ai @dccastr0 @fabayesian @MMccradden @ozanoktay__ -
AI adoption in fraud detection lags despite strong plans
By
–
83% of fraud fighters plan to add #GenAI in the next 2 years. But the reality can lag the vision: Use of AI & ML in combating #fraud has grown by just 5% in 5 years. Why? And what are the most promising anti-fraud uses for AI? New survey from @TheACFE and SAS has answers
-
Million Token Context Windows Transform RAG Deployments
By
–
You can shove in entire codebases! 1M context windows are game-changing especially for RAG-based deployments. You can just put a ton more data into the context.
-
Essential Resources for Data Science ML and AI Learning
By
–
End of this thread! If you are looking to learn more about
Data Science
ML/DL/AI
Analytics
Math & Statistics
Resources
LLMs
MLOps Then, Don't forget to follow me at @avikumart_ for upcoming posts -
Explore Data Science and Latest AI Applications on Futuresmart
By
–
Check out many blogs on wide range of data science topics to latest SOTA AI applications only on Futuresmart AI blog
-
Lower Beta Parameter Impact on Forecast Smoothing
By
–
Lower β: Impact: A lower β gives more weight to historical trend information, resulting in a smoother forecast with less sensitivity to recent trend changes.
-
Lower Alpha: Smoothing Historical Data for Forecasting
By
–
Lower α: Impact: A lower α assigns more weight to historical observations, providing smoother forecasts with less sensitivity to recent fluctuations.
-
Exponential Smoothing Alpha Parameter for Demand Forecasting Adaptation
By
–
Example: In demand forecasting for a product with rapidly changing consumer preferences, a higher α would allow the model to adapt quickly to sudden shifts in demand.