From disaster zones to underground tunnels, robots are increasingly being sent where humans cannot safely go. But many of ...
Bipolar Disorder, Digital Phenotyping, Multimodal Learning, Face/Voice/Phone, Mood Classification, Relapse Prediction, T-SNE, Ablation Share and Cite: de Filippis, R. and Al Foysal, A. (2025) ...
Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.
Abstract: In the brain-computer interface, the SSVEP (steady-state visual evoked potential) method serves to foster collaboration between humans and robots. SSVEP-based detection methods require ...
Overview: In 2025, Java is expected to be a solid AI and machine-learning language.Best Java libraries for AI in 2025 can ease building neural networks, predict ...
Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.
Researchers in Slovakia have demonstrated a machine-learning framework that predicts PV inverter output and detects anomalies using only electrical and temporal data, achieving 100% accuracy in ...
Abstract: Detection of plant disease is the most important aspect in agriculture, aimed at identifying and diagnosing disease that affect plants. If the plant disease detected earlier, that helps to ...
Antimicrobial resistance (AMR) is an increasingly dangerous problem affecting global health. In 2019 alone, ...
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