Figure 1.
Fuzzy Logic Designer Window
Figure 2.
The MFIM model's five primary steps
Figure 3.
Distribution of the tumor location. 38% (34 patients) had a tumor on their left breast alone, 29% (26 patients) had a tumor on their right breast alone, and 7% (six patients) bilateral.
Figure 4.
Gene variant distributions according to ACMG categories (P: pathogenic, LP: likely pathogenic, LB: likely benign, B: benign, VUS: variant with unknown significance).
Table 1.a.
The first example of patient data.
| Input Parameters | Sample Patient Data |
|---|---|
| Age | 51 |
| Sex | Female |
| Consanguinity | No |
| Family History | Yes |
| Membership Degree | unknown |
| Tumor Size | 10cm |
| Lymph Node | No |
| Malignancy | 2 |
| Location | Both Breast |
| Estrogen Receptor | Positive |
| Progesterone | Positive |
| Gene Variation | APC |
| Diagnosis | Positive |
| Classification | Likely Benign |
Table 1.b.
The second example of patient data.
| Input Parameters | Sample Patient Data |
|---|---|
| Age | 50 |
| Sex | Female |
| Consanguinity | No |
| Family History | Yes |
| Membership Degree | 1 |
| Tumor Size | 16cm |
| Lymph Node | No |
| Malignancy | Unknown |
| Location | Left Breast |
| Estrogen Receptor | Positive |
| Progesterone | Positive |
| Gene Variation | ATM |
| Diagnosis | Positive |
| Classification | VUS |
Table 1.c.
The third example of patient data.
| Input Parameters | Sample Patient Datas |
|---|---|
| Age | 62 |
| Sex | Female |
| Consanguinity | No |
| Family History | Yes |
| Membership Degree | 1 |
| Tumor Size | 20cm |
| Lymph Node | Unknown |
| Malignancy | Unknown |
| Location | Right Breast |
| Estrogen Receptor | Negative |
| Progesterone | Negative |
| Gene Variation | RAD50 |
| Diagnosis | Positive |
| Classification | Pathogenic |
Figure 5.
Representation of the fuzzy logic model in MATLAB, showing how 14 clinical input parameters are mapped to a single output classification. The membership functions assign degrees of belonging to each input, with values ranging from 0 to 1.
Table 2.
Membership function values in each input cluster for each risk factor.
| Risk Factors | Membership Functions | Values |
|---|---|---|
| Age | <15 | 0 |
| 16–29 | 0.25 | |
| 30–39 | 0.5 | |
| 40–59 | 0.75 | |
| >=60 | 1 | |
| Sex | Female | 1 |
| Male | 0 | |
| Consanguinity | Yes | 1 |
| No | 0 | |
| Family History | Yes | 1 |
| No | 0 | |
| Membership Degree | 0 | 0 |
| 1 & 2 | 0.5 | |
| >=3 | 1 | |
| Tumor Size | 0–19cm | 0 |
| 20–39cm | 0.5 | |
| >=40cm | 1 | |
| Lymph Node | Yes | 1 |
| No | 0 | |
| Malignancy | Grade 1 | 0 |
| Grade 2 | 0.5 | |
| Grade 3 | 1 | |
| Location | Other | 0.25 |
| Right Breast | 0.5 | |
| Left Breast | 0.75 | |
| Both Breast | 1 | |
| Estrogen Receptor | Positive | 1 |
| Negative | 0 | |
| Progesterone | Positive | 1 |
| Negative | 0 | |
| Gene Variation | TP53 | 0.1 |
| FAM175 | 0.15 | |
| RAD50 | 0.2 | |
| NBN | 0.25 | |
| MSH6 | 0.3 | |
| APC | 0.35 | |
| MSH2 | 0.4 | |
| ATM | 0.45 | |
| CDH1 | 0.5 | |
| MUTY | 0.55 | |
| PALB2 | 0.6 | |
| BLM | 0.65 | |
| MRE11A | 0.7 | |
| PMS2 | 0.75 | |
| CHEK2 | 0.8 | |
| PTEM | 0..85 | |
| BART1 | 0.9 | |
| BRIP | 1 | |
| Diagnosis | Yes | 1 |
| No | 0 | |
| Classification input and output | Benign (B) | 0 |
| Likely Benign (LB) | 0.25 | |
| VUS | 0.5 | |
| Likely Pathogenic (LP) | 0.75 | |
| Pathogenic(P) | 1 |
Figure 6.
Rules section in the Fuzzy Logic System, utilized data from 90 patients and parameters as input and membership functions within the rule section.
Table 3.
Output cluster and Values of Membership.
| Membership Functions of Output Classification | Values of Membership Functions |
|---|---|
| Benign | 0 |
| Likely Benigh | 0.25 |
| VUS (Variant with Unknown Significance) | 0.5 |
| Likely Pathogenic | 0.75 |
| Pathogenic | 1 |
Figure 7.
The set of outputs within the fuzzy logic interface on MATLAB. showing classification intervals from 0 to 1. A value of 1 corresponds to ‘Pathogenic’, 0.75 to ‘Likely pathogenic’, 0.5 to ‘VUS’, 0.25 to ‘Likely benign’, and 0 to ‘Benign’, based on ACMG classification criteria.
Table 4.
System validation results
| Risk factors | Patient 1 | Patient 2 | Patient 3 | Patient 4 | Patient 5 | Patient 6 |
|---|---|---|---|---|---|---|
| Age | 42 | 42 | 34 | 52 | 47 | 49 |
| Sex | Female | Female | Female | Female | Female | Female |
| Consanguinity | Unknown | No | Unknown | Unknown | Yes | Unknown |
| Family History | Positive | Positive | Positive | Positive | Negative | Positive |
| Tumor Size | Unknown | 1.9x1.8 | 3x2.5 | 2x2 | 1.2x0.5 | 3x2x2 |
| Membership Degree | Grade 2 | Grade 3 | Grade 2 | Grade 2 | Grade 2 | Grade 3 |
| Location | Right Breast | Right Breast | Right Breast | Left Breast | Right Breast | Left Breast |
| Estrogen receptor | Positive | Positive | Positive | Positive | Positive | Negative |
| Progesterone | Positive | Negative | Positive | Positive | Positive | Negative |
| Gene/Gene Variation | Encodes Nibrin NBN | Double Strand Break Repair Protein RAD50 | Double Strand Break Repair Protein RAD50 | DNA Mismatch Repair Protein MSH6 | Adenomatosis Polyposis Coli APC | DNA Mismatch Repair Protein MSH2 |
| Variant | c.1154_1155del | c.2014C>T | c.980G>A | c.663A>C | c.296G>A | c.435T>G |
| Diagnose | YES | YES | YES | YES | YES | YES |
| Classification | P | P | LB | LB/CIP | VUS | VUS |
| Output | P | P | LB | LB/CIP | VUS | VUS |
| Percentage Of Results | 0.92 %92 | 0.92 %92 | 0.25 %25 | 0.5 %50 | 0.5 %50 | 0.5 %50 |