How to interpret shapley force plot for feature importance?
I've never practiced this package myself, but I've read a few analyses based on SHAP, so here's what I can say:


A day_2_balance of 532 contributes to increase the predicted output. In this area, such a value of day_2_balance would let to higher predictions.
The axis scale represents the predicted output value scale. The actually predicted value is in bold font (-2.98). I don't know if the min and max values of the scale represent true min and max of the model predicted values. They more likely result from automatic scaling of the plot.
Base value should be the mean value of the estimator over the whole input space.
Those indicate the other features of which value influence the prediction to a higher value. Features are sorted by local importance, so those are features that have lower influence than those visible.
Yes, but only locally. On some other locations, you could have other contributions
higher/lower is a caption. It indicates if each feature value influences the prediction to a higher or lower output value.


From the example plot, you can draw the following interpretation: "sample n°4100 is predicted to be -2.92, which is much lower than the average predicted value (~0.643), mostly due to the specific values of features PEEP_min(5), Fi02_100_max (50), etc., and although day_2_balance is 532".