Machine learning in laboratories

Machine learning in laboratories involves computers analyzing experimental data to identify patterns and make predictions without being explicitly programmed for each task. It helps scientists interpret complex or large datasets more efficiently, guiding them in areas like drug discovery, diagnostics, or material research. By training algorithms on existing data, these systems improve their accuracy over time, supporting researchers in making informed decisions and accelerating scientific discovery.