Visual analytics systems combine machine learning or other analytic techniques with
interactive data visualization to promote sensemaking and analytical reasoning. It is through …

Nowadays, various data collected in urban context provide unprecedented opportunities for
building a smarter city through urban computing. However, due to heterogeneity, high …

This chapter focuses on describing how the human‐centered design (HCD) process can be
revisited and expanded in an artificial intelligence (AI) context, proposing a methodological …

We describe visual analytics solutions aiming to support public health professionals, and
thus, preventive measures. Prevention aims at advocating behaviour and policy changes …

Interactive machine learning (IML) is an iterative learning process that tightly couples a
human with a machine learner, which is widely used by researchers and practitioners to …

Heatmaps are a popular visualization technique that encode 2D density distributions using
color or brightness. Experimental studies have shown though that both of these visual …

The machine learning (ML) life cycle involves a series of iterative steps, from the effective
gathering and preparation of the data—including complex feature engineering processes …

Chronic tinnitus is a complex, multi-factorial symptom that requires careful assessment and
management. Evidence-based therapeutic approaches involve audiological and …

Visual analytics has been widely studied in the past decade. One key to make visual
analytics practical for both research and industrial applications is the appropriate definition …

A wide variety of predictive analytics techniques have been developed in statistics, machine
learning and data mining; however, many of these algorithms take a black-box approach in …