Hello.This is Pharmer.In this article, I will organize how much machine learning can be used in HPLC method development from ...

Researchers have developed a physics-informed machine learning framework that predicts the remaining useful life of electric ...

Chemists routinely optimize reactions to maximize the yield of their desired products, but understanding why those reactions ...

Researchers used hierarchical agglomerative clustering to sort the Veterans Health Administration's eighteen regions into ...

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...

Steatotic liver disease (SLD), formerly named fatty liver disease, has a prevalence estimated at 30–38% in adults. Detection of SLD is important, since prompt initiation of treatment can stop disease ...

How RFID and machine learning stop tool theft on construction sites, cutting $1 billion in annual losses through digital perimeters and predictive AI.

A new artificial neural-network architecture opens a window into the workings of a tool previously regarded as a black box. Since the Scientific Revolution, scientific progress has mostly been made by ...

This presentation explores how machine learning can be used to model storm surge hazards at continental and global scales. Participants will learn why broadscale storm surge information is important ...

High-precision Global Navigation Satellite System (GNSS) positioning depends on successful carrier-phase ambiguity resolution, but this remains ...