Analyst: Jennifer Fouquier


EXPLANA Description and Analysis Summary


EXPLANA Description

EXPLANA uses established machine-learning methods combined with innovative techniques to identify the most relevant features, from a variety of input features, that correlate with a response variable.

Input features and response variables can be numerical, categorical, or from non-normal data distributions. The relationships between selected features and the response can be linear or complex, non-linear relationships.

For longitudinal datasets, changes in features for each study identifier, often subjects, are calculated using different reference points to obtain delta datasets (First, Previous and Pairwise delta datasets). This is important because features in longitudinal studies can carry varying degrees of importance between models built using different reference points. EXPLANA automates feature selection from several models built using these datasets. This report was generated to textually and graphically summarize exploratory analysis and aid hypothesis generation.

Please ensure you understand the workflow, parameters/decisions, and that the percent variation explained (using out-of-bag (OOB) scores) is adequate for your purposes.

When you are using data without prior hypotheses, you are performing exploratory analysis and should make this clear when communicating results.


Response Variable: CONDITNS_13

Analysis Notes:


Methods

Feel free to use the following text, including citation information, for use in methods to ensure reproducibility:

EXPLANA was used for exploratory analysis to identify important features related to the response variable, CONDITNS_13.

A random effect of ID was used to adjust for non-independence (repeated measurements) if needed. There were 1000 trees used per Random Forest model with a max feature fraction of 0.2 of the input features for each split per decision tree in the forest. If mixed effects Random Forests were needed, 1 iterations were performed. BorutaSHAP was used to find features that perform repeatedly better than shuffled versions of all input features. Features were considered important if they performed better than 100% of the SHAP importance score of the best shuffled feature using 100 trials, p=0.05. Categorical variables were binary encoded and low occuring categorical values were not removed.

These methods are from an EXPLANA feature selection report (version: 2025.05.09) created on 2026-08-25. Additional information can be found at https://github.com/JTFouquier/explana/.


Config File

analyst: Jennifer Fouquier
response_var: CONDITNS_13
include_time: 'no'
random_effect: ID
sample_id: sample_id
timepoint: PATH
out: workflow-results/EXPLANA-NSHAP-skin-cancer-men-0.2/
iterations: '1'
n_estimators: '1000'
max_features: '0.2'
borutashap_trials: '100'
borutashap_threshold: '100'
borutashap_p: '0.05'
analyze_original: 'yes'
analyze_first: 'no'
analyze_previous: 'no'
analyze_pairwise: 'no'
absolute_values: 'no'
include_reference_values: 'no'
analysis_notes: ''
enc_percent_threshold: '0'
distance_matrices: list()
df_mod: ''
input_datasets:
  metadata:
    file_path: data/NSHAP/ICPSR_20541/DS0001/20541-0001-Data.tsv
    df_mod: "df <- df %>%\n  filter(!is.na(CONDITNS_13)) %>%\n  mutate(sample_id =
      paste(ID, PATH, sep = \"_\")) %>%\n  filter(\n    GENDER == '1',\n  ) %>%\n
      \ group_by(ID, PATH) %>%\n  slice(1) %>%\n  ungroup() %>%  \n  select(\n    -contains(\"_RECODE\"),\n
      \   -CONDITNS_14,\n    -HOWMANYC,\n    -CDIAG_1,\n    -AGEGRP,\n    -CONDITNS_18\n
      \   )\n"
    dim_method: ''
    dim_param_dict:
      method: none

Results Summary

Selected Features by Dataset

Data Original First Previous Pairwise
% Variance Explained 9.1% (11.0%) NA NA NA
N Trees 1000 NA NA NA
Feature fraction/split 0.2 NA NA NA
Max Depth 7 NA NA NA
MERF Iters. NA NA NA NA
BorutaSHAP Trials 100 NA NA NA
BorutaSHAP Threshold 100 NA NA NA
P-value 0.05 NA NA NA
N Study IDs 1454 NA NA NA
N Samples 1454 NA NA NA
Input Features 820 NA NA NA
Accepted Features 13 NA NA NA
Tentative Features 2 NA NA NA
Rejected Features 805 NA NA NA
Model Type (Pass/Fail) RF PASS; Boruta PASS Not performed Not performed Not performed

Selected feature ranks from models built using Original and, for longitudinal analyses, First, Previous and Pairwise delta datasets. Selected features are shown in black and labeled with feature rank. For true/positive instances of categorical variables (indicated with “ENC” after encoding), average impact on response is shown after the rank. For numerical features, impact is not shown because the feature relationship to response can be complex, requiring further post-hoc tests or inspection of SHAP dependence plots for additional insight. Empty grey boxes indicate features included in the model for a dataset, but not selected. Long feature names may be truncated and indicated with ellipses. A comprehensive list of input features can be found in model details below.


Original Dataset


⇨ Open File Directory

Model Summary

Data Original
Model Type (Pass/Fail) RF PASS; Boruta PASS
% Variance Explained 9.1% (11.0%)
N Trees 1000
Feature fraction/split 0.2
Max Depth 7
MERF Iters. NA
BorutaSHAP Trials 100
BorutaSHAP Threshold 100
P-value 0.05
N Study IDs 1454
N Samples 1454
Input Features 820
Accepted Features 13
Tentative Features 2
Rejected Features 805

SHAP summary beeswarm plots of feature influence on the machine learning prediction of response values. Each point represents one sample, and the horizontal position indicates impact on the response as indicated on the x-axis. Points to the left indicate a negative impact, and points to the right indicate a positive impact. The colors represent the selected feature values, where red is larger and blue is smaller. For binary encoded features (‘ENC’) red is yes[1] and blue is no[0]. SHAP is generally an improvement upon other importance scores because it provides information about both rank (how helpful the feature was compared to other features [y-axis]) and impact (a positive or negative impact on response values [x-axis]). If multiple figures are shown, scales may vary with a maximum of ten features per plot.

Selected Features

important_features decoded_features feature_importance_vals
ENC_ETHGRP_is_1 ETHGRP 0.0391
AGE AGE 0.0242
HLTHVIS HLTHVIS 0.0198
MILITARY MILITARY 0.0178
NOSE NOSE 0.0147
ENC_ETHGRP_is_2 ETHGRP 0.0134
EDUC EDUC 0.0122
HMGCOAREDUCTASEI HMGCOAREDUCTASEI 0.0107
DRUGS_COUNT DRUGS_COUNT 0.0102
INSURE_1 INSURE_1 0.0099
WEIGHT_ADJ WEIGHT_ADJ 0.0095
SEX_AGE SEX_AGE 0.0092
RESIDE RESIDE 0.0091

Feature Stats

important_features feature_importance_vals unique top freq mean std min 25% 50% 75% max
ENC_ETHGRP_is_1 0.0391 2 True 1031 NA NA NA NA NA NA NA
AGE 0.0242 NA NA 68.6829436 7.7031486 57.0000000 62.000000 68.0000000 75.000000 85.00000
HLTHVIS 0.0198 NA NA 1.9635488 2.3518846 -5.0000000 1.000000 2.0000000 3.000000 7.00000
MILITARY 0.0178 NA NA -0.5000000 2.2026543 -5.0000000 0.000000 0.0000000 1.000000 1.00000
NOSE 0.0147 NA NA -0.8370014 1.9744356 -5.0000000 0.000000 0.0000000 0.000000 1.00000
ENC_ETHGRP_is_2 0.0134 2 False 1230 NA NA NA NA NA NA NA
EDUC 0.0122 NA NA 2.6031637 1.1105530 1.0000000 2.000000 3.0000000 4.000000 4.00000
HMGCOAREDUCTASEI 0.0107 NA NA 0.3191197 0.7764286 -7.0000000 0.000000 0.0000000 1.000000 1.00000
DRUGS_COUNT 0.0102 NA NA 4.5990371 3.9579029 -7.0000000 2.000000 4.0000000 7.000000 20.00000
INSURE_1 0.0099 NA NA -0.5618982 2.2969397 -5.0000000 0.000000 0.0000000 1.000000 1.00000
WEIGHT_ADJ 0.0095 NA NA 1.0017237 0.6917767 0.1498397 0.612938 0.8294887 1.193744 11.35429
SEX_AGE 0.0092 NA NA 1.4525447 3.1984409 -5.0000000 2.000000 3.0000000 3.000000 4.00000
RESIDE 0.0091 NA NA 216.2709766 219.6537713 -5.0000000 24.000000 150.0000000 360.000000 995.00000

Input Features

input_features was_selected
FI_ID no
VERSION no
WEIGHT_SEL no
WEIGHT_ADJ yes
STRATUM no
CLUSTER no
GENDER no
AGE yes
EDUC yes
HISPANIC no
MILITARY yes
JAIL no
POLITICS no
ROSTERINTRO no
MARITLST no
SPARTNER no
SPNAMED no
SPLINENO no
OTHER_IMP no
OTHER_HH no
ALTERS no
SPTIME no
SPOPEN no
SPRELY no
SPDEMAND no
SPCRITZE no
FAMOPEN no
FAMRELY no
FAMDEMAN no
FAMCRITZ no
CLSREL no
FRAMT no
FROPEN no
FRRELY no
FRDEMN no
FRCRITZ no
SONS no
DAUGHTER no
NGRNDCLD no
VICTIM no
VOLUNTEER no
ATTEND no
SOCIAL no
RESIDEY no
RESIDEM no
RESIDE yes
NEIGHBOR_1 no
NEIGHBOR_2 no
INTERNET no
FAMDEATH no
NFAMDEATH no
FRDEATH no
NFRDEATH no
COHABOTM no
FRSTMARG no
NUMMARG no
LIVEC no
NUMLIVEC no
SEXLASTYR no
SEXIMPRT no
THINKSEX no
SEX3MOS no
WHYNOSEX_HC no
WHYNOSEX_1 no
WHYNOSEX_2 no
WHYNOSEX_2H no
WHYNOSEX_3H no
WHYNOSEX_3 no
WHYNOSEX_4 no
WHYNOSEX_5 no
WHYNOSEX_6 no
WHYNOSEX_7 no
WHYNOSEX_8 no
WHYNOSEX_9 no
WHYNOSEX_10 no
WHYNOSEX_11 no
WHYNOSEX_12 no
WHYNOSEX_13 no
WHYNOSEX_14 no
WHYNOSEX_15 no
RLTHAPPY_1 no
PHEALTH1_1 no
PHEALTH2_1 no
PMHEALH2_1 no
PMHEALH1_1 no
PEDUC_1 no
OFTSEX_1 no
VISEX_1 no
VICONDOM_1 no
ORALSEXR_1 no
ORALSEXG_1 no
OFT4PLAY_1 no
OFTSEXOK_1 no
PLEASURE_1 no
EMTSATFY_1 no
LACKSEX_1 no
NOCLMAX_1 no
CLMAXQK_1 no
SEXPAIN_1 no
SEXNOPL_1 no
ANXBSEX_1 no
NOERECT_1 no
LUBRCTE_1 no
WHRPAIN1_1 no
WHRPAIN2_1 no
WHRPAIN3_1 no
WHRPAIN4_1 no
WHRPAIN5_1 no
WHRPAIN6_1 no
WHRPAIN7_1 no
WHRPAIN8_1 no
WHRPAIN9_1 no
WHRPAIN10_1 no
WHRPAIN11_1 no
WHRPAIN12_1 no
WHRPAIN13_1 no
WHRPAIN14_1 no
WHRPAIN15_1 no
PAINBTR_1 no
LACKBTR_1 no
NCMXBTR_1 no
CMXQBTR_1 no
NPLSBTR_1 no
ANXTBTR_1 no
ERCTBTR_1 no
LUBRBTR_1 no
AVOIDSEX_1 no
SPTALKDR_1 no
SPTALKPTR_1 no
AROUSED_1 no
TINGLING_1 no
PLACKSEX_1 no
PNOCLMAX_1 no
PCLMAXQK_1 no
PSEXPAIN_1 no
PSEXNOPL_1 no
PANXBSEX_1 no
PNOERECT_1 no
PLUBRCTE_1 no
PPAIN1_1 no
PPAIN2_1 no
PPAIN3_1 no
PPAIN4_1 no
PPAIN5_1 no
PPAIN6_1 no
PPAIN7_1 no
PPAIN8_1 no
PPAIN9_1 no
PPAIN10_1 no
PPAIN11_1 no
PPAIN12_1 no
PPAIN13_1 no
PPAIN14_1 no
PPAIN15_1 no
LACKBTRU_1 no
NCMXBTRU_1 no
CMXQBTRU_1 no
NPLSBTRU_1 no
ANXBTRU_1 no
ERCTBTRU_1 no
LUBRBTRU_1 no
RELATION no
PEDUC no
SAMEBED no
SEX_OBLIG no
FORCED no
PHYSHLTH no
MNTLHLTH no
HEALTH no
EYESIGHT no
HEARLOSS no
HEARING no
SMELL no
TASTE no
SNSTOUCH no
HEARTTST no
PELVIC no
PAPSMEAR no
DYSPLAS no
TUBAL no
HYSTREC no
UTERUSR no
HAVEHYST no
OVARYR no
OVARYLRB no
REMOVARY no
BREASTR no
BRSTLRB no
LBRST no
RBRST no
BRSTSURG no
PSA no
PROSTATR no
APPROST no
PROSTOMY no
VASECTMY no
CIRCUM no
FRACTURE_1 no
FRACTURE_2 no
HEADINJ no
HEADINJ_AGE no
NOSE yes
FALLEN no
FALLEN_NUM no
ALTMEDS_1 no
ALTMEDS_2 no
ALTMEDS_3 no
ALTMEDS_4 no
ALTMEDS_5 no
ALTMEDS_6 no
ALTMEDS_7 no
ALTMEDS_8 no
ALTMEDS_9 no
HLTHPLC no
PLACETYP no
HLTHVIS yes
TALKDOC no
DISCUSS_1 no
DISCUSS_2 no
DISCUSS_3 no
DISCUSS_4 no
INSURE_1 yes
INSURE_2 no
INSURE_3 no
INSURE_4 no
INSURE_5 no
HRTPROB no
HRTFAIL no
UNCLOGA no
PAIN_WALK no
CONDITNS_1 no
CONDITNS_2 no
CONDITNS_3 no
CONDITNS_4 no
CONDITNS_5 no
CONDITNS_6 no
CONDITNS_7 no
CONDITNS_8 no
CONDITNS_9 no
CONDITNS_11 no
CONDITNS_12 no
CONDITNS_15 no
CONDITNS_16 no
CONDITNS_17 no
CDIAGM_1 no
CDIAGY_1 no
CDIAGAGE_1 no
CBEGIN_1 no
SPREAD_1 no
CDIAG_2 no
CDIAGM_2 no
CDIAGY_2 no
CDIAGAGE_2 no
CBEGIN_2 no
SPREAD_2 no
SEXCHGES no
EXERCISE no
SEX_LIMIT no
VAGINF_1 no
VAGINF_2 no
VAGINF_3 no
VAGINF_4 no
TXPREGN no
BIRTHS no
LASTPRD no
AGELSTPD no
WALKBLK no
WALKROOM no
DRESSING no
BATHING no
EATING no
INOUTBED no
TOILET no
DRIVED no
DRIVEN no
MEDDEC no
MEDDECRO no
MEDDECRE no
MEDDEC_3 no
PHYSACT no
RESTED no
HRSSLEEP no
ALCOHOL no
EVERDRNK no
DRNK3MO no
DRNKWKLY no
MNYDRINK no
MORE4DRN no
DRINK_1 no
DRINK_2 no
DRINK_3 no
DRINK_4 no
SMOKECIG no
EVERSMK no
EAVGCIG no
ELSTSMK no
EFRSTSMK no
AVECIG no
FRSTSMK no
ANYTOBAC_1 no
ANYTOBAC_2 no
ANYTOBAC_3 no
ANYTOBAC_4 no
ANYTOBAC_5 no
MEMDATE1 no
SPMSQ_ANS1A no
SPMSQ_ANS1B no
SPMSQ_ANS1C no
SPMSQ_ANS1 no
MEMDAYW1 no
SPMSQ_ANS2 no
MEMPLAC1 no
SPMSQ_ANS3 no
MEMTEL1 no
SPMSQ_ANS4 no
MEMSTRT1 no
SPMSQ_ANS4A no
MEMAGE1 no
SPMSQ_ANS5 no
MEMDOB1 no
SPMSQ_ANS6A no
SPMSQ_ANS6B no
SPMSQ_ANS6C no
SPMSQ_ANS6 no
MEMPRES1 no
SPMSQ_ANS7 no
MEMB4PR1 no
SPMSQ_ANS8 no
MEMNAME1 no
SPMSQ_ANS9 no
MEMSUBT1 no
SPMSQ_ANS10 no
SAQINTR no
MSTBATE no
MSTBATEO no
URINEPR no
FREQURIN no
OTHURINE no
FREQOTHU no
STOOLINC no
FREQSTL no
WEIGHT_INTRO no
WEIGHT no
WAIST_INTRO no
WAIST no
WAISTM no
HEIGHT_INTRO no
HEIGHT no
BMI no
BP_INTRO no
BP_1 no
SYSTOLIC_1 no
DIASTOLIC_1 no
IRREGLR_1 no
PULSE1 no
PULSE_1 no
BP_ARM_1 no
BP_INTRO_2 no
BP_2 no
SYSTOLIC_2 no
DIASTOLIC_2 no
IRREGLR_2 no
PULSE2 no
PULSE_2 no
BP_ARM_2 no
BP_INTRO_3 no
BP_3 no
SYSTOLIC_3 no
DIASTOLIC_3 no
IRREGLR_3 no
PULSE3 no
PULSE_3 no
BP_ARM_3 no
BP_TIMEH no
BP_TIMEM no
BP_TIME no
SYSTOLIC_CNT no
SYSTOLIC_MEAN no
DIASTOLIC_CNT no
DIASTOLIC_MEAN no
PULSE_CNT no
PULSE_MEAN no
SML_INTRO no
BLUEPEN_1 no
BLUEPEN_2 no
BLUEPEN_3 no
BLUEPEN_4 no
BLUEPEN_5 no
SLV_INTRO no
LASTEATH no
LASTEATM no
SLVVIAL1 no
SLTIMEH no
SLTIMEM no
SLTIMEA no
SALIVA_SAMPLE no
TESTOSTERONE_1 no
TESTOSTERONE_FLAG_1 no
TESTOSTERONE_2 no
TESTOSTERONE_FLAG_2 no
COTININE_1 no
COTININE_FLAG_1 no
COTININE_2 no
COTININE_FLAG_2 no
DHEA_1 no
DHEA_FLAG_1 no
DHEA_2 no
DHEA_FLAG_2 no
ESTRADIOL_1 no
ESTRADIOL_FLAG_1 no
ESTRADIOL_2 no
ESTRADIOL_FLAG_2 no
PROGESTERONE_1 no
PROGESTERONE_FLAG_1 no
PROGESTERONE_2 no
PROGESTERONE_FLAG_2 no
COTEPA_M no
COTEPA_F no
DRUGS_INTRO no
DRUGS_COUNT yes
DRUGS_COUNT_FLAG no
NP_COUNT no
UNIDENT_COUNT no
ANTIINFECTIVES no
AMEBICIDES no
ANTIFUNGALS no
ANTIMALARIALAGEN no
ANTITUBERAGENTS no
CEPHALOSPORINS no
LEPROSTATICS no
MACROLIDEDERIVAT no
MISCANTIBIOTICS no
PENICILLINS no
QUINOLONES no
SULFONAMIDES no
TETRACYCLINES no
URINARYANTIINFEC no
ANTIHYPLIPAGENTS no
ANTINEOPLASTICS no
ALKYLATINGAGENTS no
ANTIMETABOLITES no
HORMONESANTINEOP no
MISCANTINEOPLAST no
BIOLOGICALS no
RECOMBINANTHUMAN no
CARDIOVASCULARAG no
ANGIOTENSINCONVE no
ANTIADRENERGPERI no
ANTIADRENERGCENT no
ANTIANGINALAGENT no
ANTIARRHYTHMICAG no
BETAADRENERGICBL no
CALCIUMCHANNELBL no
DIURETICS no
INOTROPICAGENTS no
MISCCARDIOVASCUL no
PERIPHERALVASODI no
VASODILATORS no
VASOPRESSORS no
ANTIHYPERTENSIVE no
ANGIOTENSINIIINH no
CENTRALNERVOUSSY no
ANALGESICS no
MISCANALGESICS no
NARCANALGS no
NONSTEROIDALANTI no
SALICYLATES no
ANALGESICCOMBINA no
ANTICONVULSANTS no
ANTIEMETICANTIVE no
ANTIPARKINSONAGE no
ANXIOLYTICSSEDAT no
BARBITURATES no
BENZODIAZEPINES no
MISCANXIOLYTICSS no
CNSSTIMULANTS no
MUSCLERELAXANTS no
MISCANTIDEPRESSA no
MISCANTIPSYCHOTI no
PSYCHOTHERCOMBIN no
MISCCENTRALNERVO no
COAGULATIONMODIF no
ANTICOAGULANTS no
ANTIPLATELETAGEN no
MISCCOAGULATIONM no
GASTROINTESTINAL no
ANTACIDS no
ANTICHOLSANTISPA no
ANTIDIARRHEALS no
DIGESTIVEENZYMES no
GALLSTONESOLUBIL no
GISTIMULANTS no
H2ANTAGONISTS no
LAXATIVES no
MISCGIAGENTS no
HORMONES no
ADRENALCORTICALS no
ANTIDIABETICAGEN no
MISCHORMONES no
SEXHORMONES no
CONTRACEPTIVES no
THYROIDDRUGS no
IMMUNOSUPPRESSIV no
MISCAGENTS no
ANTIDOTES no
CHELATINGAGENTS no
CHOLINERGICMUSCL no
LOCALINJECTABLEA no
MISCUNCATEGORIZE no
GENITOURINARYTRA no
NUTRITIONALPRODS no
IRONPRODUCTS no
MINERALSANDELECT no
VITAMINS no
VITAMINMINERAL no
RESPIRATORYAGENT no
ANTIHISTAMINES no
ANTITUSSIVES no
BRONCHODILATORS no
METHYLXANTHINES no
DECONGESTANTS no
EXPECTORANTS no
MISCRESPIRATORYA no
RESPIRATORYINHAL no
UPPERRESPIRATORY no
TOPICALAGENTS no
DERMATOLOGICALAG no
TOPICALANTIINFEC no
TOPICALSTEROIDS no
TOPICALANESTHETI no
MISCTOPICALAGENT no
TOPICALACNEAGENT no
MOUTHANDTHROATPR no
OPHTHALPREPARATI no
OTICPREPARATIONS no
VAGINALPREPARATI no
LOOPDIURETICS no
POTASSIUMSPARING no
THIAZIDEDIURETIC no
CARBONICANHYDRAS no
FIRSTGENERATIONC no
THIRDGENERATIONC no
OPHTHALANTIINFEC no
OPHTHALGLAUCOMAA no
OPHTHALSTEROIDS no
OPHTHALSTEROIDSW no
OPHTHALANTIINFLA no
MISCOPHTHALAGENT no
OTICSTEROIDSWITH no
MISCOTICAGENTS no
HMGCOAREDUCTASEI yes
MISCANTIHYPLIPAG no
SKELMUSCRELS no
ADRENERGICBRONCH no
BRONCHODILATORCO no
ANDROGENSANDANAB no
ESTROGENS no
PROGESTINS no
SEXHORMONECOMBIN no
NARCANALGCOMBINA no
ANTIRHEUMATICS no
ANTIMIGRAINEAGEN no
ANTIGOUTAGENTS no
FIVEHT3RECEPTORA no
PHENTHIAZANTIEME no
ANTICHOLANTIEMET no
MISCANTIEMETICS no
HYDANTOINANTICON no
BARBITURATEANTIC no
BENZODIAZEPINEAN no
MISCANTICONVULSA no
ANTICHOLANTIPARK no
SSRIANTIDEPRESSA no
TRICYCLICANTIDEP no
PHENTHIAZANTIPSY no
PLATELETAGGREGAT no
SULFONYLUREAS no
NONSULFONYLUREAS no
INSULIN no
ALPHAGLUCOSIDASE no
BISPHOSPHONATES no
ALTERNATIVEMEDS no
NUTRACEUTICALS no
HERBALPRODUCTS no
PENICILLINASERES no
AMINOPENICILLINS no
BETALACTAMASEINH no
ADAMANTANEANTIVI no
PURINENUCLEOSIDE no
MISCANTITUBERAGE no
POLYENES no
AZOLEANTIFUNGALS no
MISCANTIFUNGALS no
ANTIMALARIALQUIN no
MISCANTIMALARIAL no
LINCOMYCINDERIVA no
FIBRICACIDDERIVA no
PSYCHOTHERAGENTS no
LEUKOTRIENEMODIF no
NASALLUBRICANTS no
NASALSTEROIDS no
NASALANTIHISTAMI no
NASALPREPARATION no
ANTIDEPRESSANTS no
MONOAMINEOXIDASE no
ANTIPSYCHOTICS no
BILEACIDSEQUESTR no
ANOREXIANTS no
IMMUNOLOGICAGENT no
MONOCLONALANTIBO no
HEPARINS no
COUMARINSANDINDA no
IMPOTENCEAGENTS no
URINARYANTISPASM no
URINARYPHMODIFIE no
MISCGENITOURINAR no
OPHTHALANTIHISTA no
MISCVAGINALAGENT no
ANTIPSORIATICS no
THIAZOLIDINEDION no
PROTONPUMPINHIBI no
CARDIOSELECTIVEB no
NONCARDIOSELECTI no
DOPAMINERGICANTI no
FIVEAMINOSALIC no
COX2INHIBITORS no
MEGLITINIDES no
FIVEALPHAREDUCTI no
ANTIHYPERURICEMI no
TOPICALANTIBIOTI no
TOPICALANTIFUNGA no
INHALEDCORTICOST no
MASTCELLSTABILIZ no
ANTICHOLBRONCHOD no
GLUCOCORTICOIDS no
MINERALOCORTICOI no
AGENTSFORPULMONA no
MACROLIDES no
KETOLIDES no
PHENYLPIPERAZINE no
TETRACYCLICANTID no
SSNRIANTIDEPRESS no
MISCANTIDIABETIC no
DIBENZAZEPINEANT no
CHOLINERGICAGONI no
CHOLINESTERASEIN no
ANTIDIABETICCOMB no
CHOLESTEROLABSOR no
ANTIHYPLIPCOMBIN no
SMOKINGCESSATION no
OTHERSUPPLEMENTS no
TST_INTRO no
TASTE_1 no
TASTEID_1 no
TASTEID_FLAG_1 no
TASTE_2 no
TASTEID_2 no
TASTEID_FLAG_2 no
TASTE_3 no
TASTEID_3 no
TASTEID_FLAG_3 no
TASTE_4 no
TASTEID_4 no
TASTEID_FLAG_4 no
VS_INTRO no
BLUESWAB no
STMSWAB no
BVYSWAB no
BV no
BVCAT no
BV_FLAG no
YEAST no
CYTLSENT no
BASAL_PARABASAL no
INTERMEDIATE no
SUPERFICIAL no
MATURATION no
DV_INTRO no
DVDISTCE no
DVLINE no
GLASSES no
GUP_INTRO no
GUPSTAND no
B3TIME1 no
B3TIME2 no
B3TIME3 no
GUPPROB_1 no
GUPPROB_2 no
GUPPROB_3 no
GUPPROB_4 no
GUPPROB_5 no
TOUCH_INTRO no
PT_12MM no
PT_DUMMY no
PT_8MM no
PT_4MM no
HAND2PT no
BS_INTRO no
BLDSPOT no
NUM_BS no
BLDPRICK no
BS_SAMPLE no
CRP no
CRP_FLAG no
EBV no
EBV_FLAG no
HB no
HB_FLAG no
HBA1C no
HBA1C_FLAG no
HAPPY no
SLFESTEM no
NOTEAT no
FLTDEP no
FLTEFF no
NOSLEEP no
WASHAPY no
WASLONLY no
UNFRIEND no
ENJLIFE no
FLTSAD no
DISLIKD no
NOTGETGO no
FLTTENS no
FRIGHT no
WORRY no
RELAXED no
BUTRFLY no
RESTLES no
PANIC no
UNCNTRL no
CONFIDNT no
GOMYWAY no
PILEDIFF no
COMPANION no
LEFTOUT no
ISOLATED no
JOBSTAT_1 no
JOBSTAT_2 no
JOBSTAT_3 no
JOBSTAT_4 no
JOBSTAT_5 no
JOBSTAT_6 no
WORKPAY no
FULLPART no
WEEKPAY no
HRSCJOB no
IML50K no
IML25K no
IML100K no
INCOME_1 no
INCOME_2 no
HAML50K no
HAML10K no
HAML500K no
HAML100K no
RELIGION no
BRANCH no
BORNAGN no
ATNDSERV no
BELIEFS no
TOUCHPET no
EMBRACE no
PLAYCHLD no
HUGPTNR no
HUGHOLD no
CAREGIVER no
CARE_REL no
CARE_AGE no
CARE_RSN no
CARE_PRIM no
CARE_MST no
CARE_DAY no
CARE_HRS no
INFIDELITY_1 no
INFIDELITY_2 no
INFIDELITY_3 no
SEX_LOVE no
SEX_RELIG no
SEX_MAINT no
SEX_AGE yes
PERSPRES no
CANDID no
RFHLTHR no
RFHLTH2R no
RFHLTH3R no
RDESCR1 no
RDESCR2 no
RDESCR3 no
RDESCR4 no
RDESCR5 no
RDESCR6 no
RDESCR7 no
IWLOC1 no
IWLOC2 no
IWLOC3 no
IWLOC4 no
IWLOC5 no
IWLOC6 no
IWLOC7 no
STRUCTQ no
BUILD no
OTBUILD no
COMBUILD no
CASECOMP no
CASEDIF no
ENC_INT_START_is_2005m10 no
ENC_INT_START_is_2005m11 no
ENC_INT_START_is_2005m12 no
ENC_INT_START_is_2005m7 no
ENC_INT_START_is_2005m8 no
ENC_INT_START_is_2005m9 no
ENC_INT_START_is_2006m1 no
ENC_INT_START_is_2006m2 no
ENC_INT_START_is_2006m3 no
ENC_ETHGRP_is_1 yes
ENC_ETHGRP_is_2 yes
ENC_ETHGRP_is_3 no
ENC_ETHGRP_is_4 no
ENC_ETHGRP_is_NA no

Log


Binary encoded columns created for categorical input variables:

 ->  INT_START: ['ENC_INT_START_is_2005m10', 'ENC_INT_START_is_2005m11', 'ENC_INT_START_is_2005m12', 'ENC_INT_START_is_2005m7', 'ENC_INT_START_is_2005m8', 'ENC_INT_START_is_2005m9', 'ENC_INT_START_is_2006m1', 'ENC_INT_START_is_2006m2', 'ENC_INT_START_is_2006m3']

 ->  ETHGRP: ['ENC_ETHGRP_is_1', 'ENC_ETHGRP_is_2', 'ENC_ETHGRP_is_3', 'ENC_ETHGRP_is_4', 'ENC_ETHGRP_is_NA']

BorutaSHAP Figures

⇨ Open PDF in new window


First Delta Dataset


⇨ Open File Directory

Results

Model Summary

Data First
Model Type (Pass/Fail) Not performed
% Variance Explained NA
N Trees NA
Feature fraction/split NA
Max Depth NA
MERF Iters. NA
BorutaSHAP Trials NA
BorutaSHAP Threshold NA
P-value NA
N Study IDs NA
N Samples NA
Input Features NA
Accepted Features NA
Tentative Features NA
Rejected Features NA

Selected Features

important_features decoded_features feature_importance_vals
no_selected_features NA -100

Feature Stats

Analysis not completed

Input Features

Analysis not completed

Interpretation/Literature Search

The following links can help with hypothesis generation. Names of variables likely need modification.

important_features url
no_selected_features https://pubmed.ncbi.nlm.nih.gov/?term=no_selected_features%20AND%20CONDITNS_13

Log

BorutaSHAP Figures

⇨ Open PDF in new window


Previous Delta Dataset


⇨ Open File Directory

Model Summary

Data Previous
Model Type (Pass/Fail) Not performed
% Variance Explained NA
N Trees NA
Feature fraction/split NA
Max Depth NA
MERF Iters. NA
BorutaSHAP Trials NA
BorutaSHAP Threshold NA
P-value NA
N Study IDs NA
N Samples NA
Input Features NA
Accepted Features NA
Tentative Features NA
Rejected Features NA

Selected Features

important_features decoded_features feature_importance_vals
no_selected_features NA -100

Feature Stats

Analysis not completed

Input Features

Analysis not completed

Interpretation/Literature Search

The following links can help with hypothesis generation. Names of variables likely need modification.

important_features url
no_selected_features https://pubmed.ncbi.nlm.nih.gov/?term=no_selected_features%20AND%20CONDITNS_13

Log

BorutaSHAP Figures

⇨ Open PDF in new window


Pairwise Delta Dataset


⇨ Open File Directory

Model Summary

Data Pairwise
Model Type (Pass/Fail) Not performed
% Variance Explained NA
N Trees NA
Feature fraction/split NA
Max Depth NA
MERF Iters. NA
BorutaSHAP Trials NA
BorutaSHAP Threshold NA
P-value NA
N Study IDs NA
N Samples NA
Input Features NA
Accepted Features NA
Tentative Features NA
Rejected Features NA

Selected Features

important_features decoded_features feature_importance_vals
no_selected_features NA -100

Feature Stats

Analysis not completed

Input Features

Analysis not completed

Interpretation/Literature Search

The following links can help with hypothesis generation. Names of variables likely need modification.

important_features url
no_selected_features https://pubmed.ncbi.nlm.nih.gov/?term=no_selected_features%20AND%20CONDITNS_13

Log

BorutaSHAP Figures

⇨ Open PDF in new window


See the Github repository for more information.