Publications by authors named "Dimitrios Bakalis"
The objective of this study was to evaluate the effectiveness of machine learning classification techniques applied to nerve conduction studies (NCS) of motor and sensory signals for the automatic diagnosis of carpal tunnel syndrome (CTS). Two methodologies were tested. In the first methodology, motor signals recorded from the patients' median nerve were transformed into time-frequency spectrograms using the short-time Fourier transform (STFT).
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- Non-steroidal anti-inflammatory drugs, while effective for inflammation, carry risks of negative side effects, leading to interest in compounds that blend anti-inflammatory and antioxidant properties.
- The study utilized deep learning, specifically a one-dimensional convolutional neural network, to classify and predict the efficacy of compounds that inhibit inflammatory enzymes and scavenge free radicals.
- The results showed high accuracy in identifying dual active compounds and in predicting the effectiveness of newly synthesized anti-inflammatory agents, aiding in future therapeutic applications.