R9212/get_sepsis_score.m
5fffa754af2cmaster

get_sepsis_score.m
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			function [score, label] = get_sepsis_score(current_data, model)
			N_features = 40;

			th = 195;

			load('median_values.mat')
			gender_column = 36;
			label_gender = current_data(1, gender_column);

			switch label_gender
			case 0
			median_values = median_values_females;
			case 1
			median_values = median_values_males;
			end

			current_data = current_data(:, 1:N_features);

			for k = 1 : N_features
			if isnan(current_data(1, k))
			i1 = find(~isnan(current_data(:, k)), 1);
			if isempty(i1)
			current_data(1, k) = median_values(k);
			else
			current_data(1, k) = current_data(i1, k);
			end
			end
			end

			data_filled = fillmissing(current_data, 'previous', 1);
			win = size(current_data, 1);

			[label_vector, scores_full] = predict(model.model, data_filled(end-win+1:end,:));

			if (label_vector(end) <= th)
			label = 1;
			score = 1;
			else
			K = [];
			i = 1;
			while (i - 8 + win <= 8)
			K = [K; i-7:1:i-8+win];
			i = i + 1;
			end

			F = zeros(size(K, 1), 1);

			for t = 1 : size(K, 1)
			score_nonsep_loss = loss(model.gprMdl_nonsepsis_score, K(t, :)', scores_full);
			score_sep_loss = loss(model.gprMdl_sepsis_score, K(t, :)', scores_full);
			[~, ind_min] = min([score_nonsep_loss score_sep_loss]);
			F(t) = ind_min;
			end

			sep_det_flag = numel(find(F == 2));

			if sep_det_flag
			label = 1;
			score = 1;
			else
			label = 0;
			score = 0;
			end
			end

			end