From Code to Career: Assessing Competitive Programmers for Industry Placement

Automated chart classification plays a crucial role in efficient data extraction and interpretation in scientific research, especially in Quantitative Systems Pharmacology (QSP)<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup><sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup>QSP: Quantitative System Pharmacology and Physiologically Based Pharmacokinetic (PBPK)<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup><sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>PBPK: Physiologically-Based Pharmacokinetic modeling. In the development of PBPK model building, researchers often perform extensive literature searches to gather essential parameters and clinical data from graphical formats. Since scientific data are often presented in graphical formats such as lines, bars, pie charts and tables, accurate classification of these chart types is essential for effective data extraction. Although various online tools such as Engauge Digitizer and WebPlotDigitizer are widely used to manually digitize graph data, an automated classification approach can further streamline data extraction…