Diagnostic Captioning is described as the automatic text generation from a collection of X-RAY images and it can assist inexperienced doctors and radiologists to reduce clinical errors or help experienced professionals to increase their productivity. Therefore, tools that would help doctors and radiologists produce higher quality reports in less time could be of high interest for medical imaging departments, as well as significantly impact deep learning research within the biomedical domain. With our participation in ImageCLEFmedical 2022 Caption evaluation campaign, we have attempted to address both concept detection and caption prediction tasks by developing baselines based on Deep Neural Networks; including image encoders, classifiers and text generators. Our group, NeuralDynamicsLab at KTH Royal Institute of Technology, within the school of Electrical Engineering and Computer Science, ranked 4th in the former and 5th in the latter task.