Conditional sentence | EPFL Graph Search

Conditional sentences are natural language sentences that express that one thing is contingent on something else, e.g. "If it rains, the picnic will be cancelled." They are so called because the impact of the main clause of the sentence is conditional on the dependent clause. A full conditional thus contains two clauses: a dependent clause called the antecedent (or protasis or if-clause), which expresses the condition, and a main clause called the consequent (or apodosis or then-clause) expressing the result. Languages use a variety of grammatical forms and constructions in conditional sentences. The forms of verbs used in the antecedent and consequent are often subject to particular rules as regards their tense, aspect, and mood. Many languages have a specialized type of verb form called the conditional mood – broadly equivalent in meaning to the English "would (do something)" – for use in some types of conditional sentences. There are various ways of classifying conditional sentences. Many of these categories are visible cross-linguistically. A conditional sentence expressing an implication (also called a factual conditional sentence) essentially states that if one fact holds, then so does another. (If the sentence is not a declarative sentence, then the consequence may be expressed as an order or a question rather than a statement.) The facts are usually stated in whatever grammatical tense is appropriate to them; there are not normally special tense or mood patterns for this type of conditional sentence. Such sentences may be used to express a certainty, a universal statement, a law of science, etc. (in these cases if may often be replaced by when): If you heat water to 100 degrees (°C) , it boils. If the sea is stormy, the waves are high. They can also be used for logical deductions about particular circumstances (which can be in various mixtures of past, present, and future): If it's raining here now, then it was raining on the West Coast this morning. If it's raining now, then your laundry is getting wet.

BPMN process generation and optimization for readability in the context of telemedecine

Charline Montial

In business, automated processes can be specified using the BPMN standard, which stands for Business Process Model and Notation. It is presented as flowcharts with standardized graphical elements to show the possible flows and activities of a process. These diagrams can be seen as a graph with logical expressions conditioning their edges. The telemedecine start-up Soignez-moi.ch uses BPMN to describe complex medical forms in a readable way. Soignez-moi.ch offers medical consultations via an online platform. The first step for the patient is to fill a questionnaire about his/her symptoms. In the second step, a doctor accesses to the answers and proceeds to call the patient for the teleconsultation. The complexity of these medical forms comes from the fact that the questions are adapted to the patient answers, which leads to different possible flows. Complex forms from another telemedecine website, Diaana, had to be translated to BPMN to be compatible and used at Soignez-moi.ch. Diaana is a contraction of the words diagnosis and anamnesis. The way these forms are specified is very different from what has been modeled in Soignez-moi.ch: instead of having separated branches, there is a sequential list of questions. In this list, every question is evaluated on its own to see if it is asked or not. The question conditions are Boolean expressions. If a direct translation to BPMN is performed, there is no branching to show the relationships between the questions. The aim of my work is to highlight similarities in the branch conditions to make the diagrams more readable and editable by humans. Doctors and collaborators read the medical BPMN processes and may modify them. It should be a pleasant experience for them to go through the diagrams. They should quickly understand in a visual way if questions are related, and how they are related. The BPMN process readability has been achieved by extracting patterns, showing the implications between the questions to have a readable diagram with meaningful branches. This translation has been applied to 18 questionnaires. Two questionnaires were not improved because they were only composed of one question. One questionnaire was also not improved because all its questions were unconditional, meaning that no relationship between the question conditions could be highlighted. Another questionnaire with conditional questions was not improved because its conditions were unrelated. 14/18 questionnaires have had their readability improved.

2022

BPMN process generation and optimization for readability in the context of telemedecine

Charline Montial

2022