Narrow Results

We present a fully automated AI-based system for intensive monitoring of cognitive symptoms of neurotoxicity that frequently appear as a result of immunotherapy of hematologic malignancies. Early manifestations of these symptoms are evident in the patient’s speech in the form of mild aphasia and confusion and can be detected and effectively treated prior to onset of more serious and potentially life-threatening impairment. We have developed the Automated Neural Nursing Assistant (ANNA) system designed to conduct a brief cognitive assessment several times per day over the telephone for 5-14 days following infusion of the immunotherapy medication. ANNA uses a conversational agent based on a large language model to elicit spontaneous speech in a semi-structured dialogue, followed by a series of brief language-based neurocognitive tests. In this paper we share ANNA’s design and implementation, results of a pilot functional evaluation study, and discuss technical and logistic challenges facing the introduction of this type of technology in clinical practice. A large-scale clinical evaluation of ANNA will be conducted in an observational study of patients undergoing immunotherapy at the University of Minnesota Masonic Cancer Center starting in the Fall 2023.

In resent years, speech emotion recognition has attracted more and more attention. In this paper, we extracted a new emotion feature named as the Long-term Rise Zero-Crossing Interval (LRZCI). The support vector machine (SVM) is used as classifier. Recognition experiments are conducted on the Danish Emotion Speech (DES) Database. Experimental results illustrate the validity of the kind of feature.

The aim of this chapter is to refine some questions regarding AI, and to provide partial answers to them. We analyze the state of the art in designing intelligent systems that are able to mimic human complex activities, including acts based on artificial consciousness. The analysis is performed to contrast the human cognition and behavior to the similar processes in AI systems. The analysis includes elements of psychology, sociology, and communication science related to humans and lower level beings. The second part of this chapter is devoted to human-human and man-machine communication, as related to intelligence. We emphasize that the relational aspects constitute the basis for the perception, knowledge, semiotic and communication processes. Several consequences are derived. Subsequently, we deal with the tools needed to endow the machines with intelligence. We discuss the roles of knowledge and data structures. The results could help building "sensitive and intelligent" machines.