Deep learning-based methods, devices, and systems for prenatal testing

A method, comprising:

• (a) amplifying at least a portion of circulating cell-free nucleic acid molecules of a sample obtained from a subject to generate amplified cell-free nucleic acid molecules;
• (b) sequencing at least a portion of the amplified cell-free nucleic acid molecules to produce a set of sequencing reads;
• (c) processing the set of sequencing reads to generate a probability value using a machine learning algorithm, wherein the probability value indicates a presence or absence of a plurality of nucleic acid methylation markers in the set of sequencing reads, and wherein the machine learning algorithm is trained using an input data set comprising one or more nucleic acid methylation markers of one or more sets of sequencing reads from at least one healthy subject and at least one diseased subject;
• and
• (d) detecting a presence of a disease of the subject when the probability value exceeds a threshold value of the machine learning algorithm indicating the presence of the disease of the subject.