OSCR

Chronological Diagnostic Algorithm Predicting Neuropathology in Parkinsonism.

Code ↔ Paper

2 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 2 matches
  1. [1] § Results › Progression of the Diseases ↔ chronognosis/chronognosis.py, lines 130–189 · score 0.78 · sleep behavior disorder, upper motor neuron, eye movement, hyposmia, postural, RBD
  2. [2] § Results › Progression of the Diseases ↔ chronognosis/chronognosis.py, lines 130–189 · score 0.72 · sleep behavior disorder, upper motor neuron, eye movement, UMN, postural, RBD

Paper

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The authors' code

Python · 263 lines · 13 KB · Apache-2.0 · 2 matches

  1. import os
  2. import warnings
  3. import pandas as pd
  4. import shap
  5. from catboost import CatBoostClassifier, Pool
  7. # Suppress warnings
  8. warnings.simplefilter('ignore')
  10. def main(root, input_path, yr_th):
  11. dx_list = [
  12. 'LBD', 'LBD-AD', 'PSP', 'PSP-AD', 'PSP-LBD', 'MSA', 'CBD', 'AD', 'FTLD'
  13. ]
  14. label_dict = {label: idx for idx, label in enumerate(dx_list)}
  15. int_dict = {value: key for key, value in label_dict.items()}
  18. rename_dict = {
  19. 'Age_onset': 'Age at onset (yr)',
  20. 'EOMI_onset': 'EOM restriction',
  21. 'hypomimia_onset': 'Hypomimia',
  22. 'masked_face_onset': 'Masked face',
  23. 'bradykinesia_onset': 'Bradykinesia',
  24. 'slow_movement_onset': 'Slow movement',
  25. 'decreased_arm_swing_onset': 'Decreased arm swing',
  26. 'micrographia_onset': 'Micrographia',
  27. 'small_handwrtiting_onset': 'Small handwrtiting',
  28. 'akinesia_onset': 'Akinesia',
  29. 'no_spontaneous_movements_onset': 'No spontaneous movements',
  30. 'gait_freezing_onset': 'Gait freezing',
  31. 'glued_gait_onset': 'Glued gait',
  32. 'magnetic_gait_onset': 'Magnetic gait',
  33. 'rigidity_onset': 'Rigidity',
  34. 'axial_rigidity_onset': 'Axial rigidity',
  35. 'nuchal__neck__rigidity_onset': 'Nuchal neck rigidity',
  36. 'appendicular__limb__rigidity_onset': 'Appendicular limb rigidity',
  37. 'cogwheel_rigidity_onset': 'Cogwheel rigidity',
  38. 'stiffness_onset': 'Stiffness',
  39. 'increased_muscle_tone_onset': 'Increased muscle tone',
  40. 'the_fact_patient_fell__not_risk_of_fall_onset': 'Fall',
  41. 'early_falls_onset': 'Early falls',
  42. 'multiple_frequent_falls_onset': 'Multiple frequent falls',
  43. 'falling_forwards_onset': 'Falling forwards',
  44. 'positive_pull_test_onset': 'Positive pull test',
  45. 'falling_backwards_onset': 'Falling backwards',
  46. 'imbalance_onset': 'Imbalance',
  47. 'shuffling_gait_onset': 'Shuffling gait',
  48. 'festinating_gait_onset': 'Festinating gait',
  49. 'turning_en_bloc_onset': 'Turning en bloc',
  50. 'stooped_posture_onset': 'Stooped posture',
  51. 'pisa_sign_onset': 'Pisa sign',
  52. 'camptocormia_onset': 'Camptocormia',
  53. 'scoliosis_onset': 'Scoliosis',
  54. 'memory_loss__deficit_onset': 'Memory loss deficit',
  55. 'memory_loss_deficit_benefited_by_cues_onset': 'Memory loss deficit benefited by cues',
  56. 'amnesia_onset': 'Amnesia',
  57. 'word_finding_difficulty_onset': 'Word finding difficulty',
  58. 'dysorientation_onset': 'Disorientation',
  59. 'lost_date_onset': 'Lost date',
  60. 'lost_name_onset': 'Lost name',
  61. 'lost_place_onset': 'Lost place',
  62. 'impaired_serial_sevens_onset': 'Impaired serial sevens',
  63. 'abnormal_clock_test_onset': 'Abnormal clock test',
  64. 'impaired_spelling_WORLD_backwards_onset': 'Impaired spelling world backwards',
  65. 'wander_onset': 'Wander',
  66. 'gets_lost_onset': 'Gets lost',
  67. 'prosopagnosia_onset': 'Prosopagnosia',
  68. 'unable_to_answer_famous_faces_onset': 'Unable to answer famous faces',
  69. 'fluctuation_of_neuropsychiatric_symptoms_onset': 'Fluctuation of neuropsychiatric symptoms',
  70. 'sundowning_onset': 'Sundowning',
  71. 'hallucinations_onset': 'Hallucinations',
  72. 'visual_hallucinations_onset': 'Visual hallucinations',
  73. 'paranoid_delusions_onset': 'Paranoid delusions',
  74. 'apathy_onset': 'Apathy',
  75. 'social_withdrawal_onset': 'Social withdrawal',
  76. 'abulia_onset': 'Abulia',
  77. 'bradyphrenia_onset': 'Bradyphrenia',
  78. 'dysececutive_syndrome_onset': 'Dysexecutive syndrome',
  79. 'change_in_personality_onset': 'Change in personality',
  80. 'disinhibition_onset': 'Disinhibition',
  81. 'impulsivity_onset': 'Impulsivity',
  82. 'obsession_onset': 'Obsession',
  83. 'compulsivity_onset': 'Compulsivity',
  84. 'hyperorality_onset': 'Hyperorality',
  85. 'abnormally_increased_appetite_onset': 'Abnormally increased appetite',
  86. 'hyperphagia_onset': 'Hyperphagia',
  87. 'perseveration_onset': 'Perseveration',
  88. 'echolalia_onset': 'Echolalia',
  89. 'palilalia_onset': 'Palilalia',
  90. 'groping_onset': 'Groping',
  91. 'speaking_out_of_turn_onset': 'Speaking out of turn',
  92. 'stereotyped_behavior_onset': 'Stereotyped behavior',
  93. 'joking_jovial_behavior_onset': 'Joking jovial behavior',
  94. 'kleptomania_stealing_onset': 'Kleptomania stealing',
  95. 'cussing_behavior_onset': 'Cussing behavior',
  96. 'hypersexuality_onset': 'Hypersexuality',
  97. 'caught_in_a_scam_fraud_onset': 'Caught in a scam fraud',
  98. 'gambling_onset': 'Gambling',
  99. 'addiction_abuse_onset': 'Addiction abuse',
  100. 'Baker_acted_onset': 'Baker acted',
  101. 'suicidal_ideation_onset': 'Suicidal ideation',
  102. 'criminal_behavior_onset': 'Criminal behavior',
  103. 'hospitalized_in_psychiatric_ward_asylum_onset': 'Hospitalized in psychiatric ward asylum',
  104. 'positive_grasping_reflex_onset': 'Positive grasping reflex',
  105. 'positive_snout_reflex_onset': 'Positive snout reflex',
  106. 'positive_sucking_reflex_onset': 'Positive sucking reflex',
  107. 'positive_palmomental_reflex_onset': 'Positive palmomental reflex',
  108. 'frontal_release_sign_onset': 'Frontal release sign',
  109. 'gegenhalten_onset': 'Gegenhalten',
  110. 'paratonia_onset': 'Paratonia',
  111. 'abnormal_Luria_test_onset': 'Abnormal luria test',
  112. 'abnormal_fist_edge_palm_test_onset': 'Abnormal fist edge palm test',
  113. 'applause_sign_onset': 'Applause sign',
  114. 'abnormal_go_no_go_test_onset': 'Abnormal go no go test',
  115. 'stopped_driving_onset': 'Stopped driving',
  116. 'car_accident_onset': 'Car accident',
  117. 'metamorphosis_onset': 'Metamorphosis',
  118. 'loss_of_appetite_onset': 'Loss of appetite',
  119. 'cries_a_lot_onset': 'Cries a lot',
  120. 'aphasia_primary_progressive_aphasia__PPA__onset': 'Aphasia primary progressive aphasia (PPA)',
  121. 'agrammatic_aphasia_onset': 'Agrammatic aphasia',
  122. 'reduced_fluency_onset': 'Reduced fluency',
  123. 'apraxia_of_speech_onset': 'Apraxia of speech',
  124. 'abnormal_articulation_pronunciation_onset': 'Abnormal articulation pronunciation',
  125. 'jumbled_speech_onset': 'Jumbled speech',
  126. 'spasmodic_speech_dysphornia_onset': 'Spasmodic speech dysphonia',
  127. 'mutism_onset': 'Mutism',
  128. 'alien_hand_or_limb_onset': 'Alien hand or limb',
  129. 'orobuccal_apraxia_onset': 'Orobuccal apraxia',
  130. 'apraxia_onset': 'Apraxia',
  131. 'ideomotor_apraxia_onset': 'Ideomotor apraxia',
  132. 'cannot_pantomime_onset': 'Cannot pantomime',
  133. 'limb_apraxia_onset': 'Limb apraxia',
  134. 'unable_to_stick_out_tongue_onset': 'Unable to stick out tongue',
  135. 'unable_to_lick_lips_onset': 'Unable to lick lips',
  136. 'unable_to_wristle_onset': 'Unable to whistle',
  137. 'simultanagnosia_onset': 'Simultanagnosia',
  138. 'cortical_sensory_deficit_onset': 'Cortical sensory deficit',
  139. 'REM_sleep_behavior_disorder__RBD__onset': 'RBD',
  140. 'hyposmia_onset': 'Hyposmia',
  141. 'loss_of_smell_onset': 'Loss of smell',
  142. 'restricted_eye_movement_gaze_palsy_onset': 'Restricted eye movement gaze palsy',
  143. 'vertical_hypometric_saccades_onset': 'Vertical hypometric saccades',
  144. 'downgaze_palsy_onset': 'Downgaze palsy',
  145. 'slow_saccades_onset': 'Slow saccades',
  146. 'eyelid_opening_apraxia_onset': 'Eyelid opening apraxia',
  147. 'blepharospasm_onset': 'Blepharospasm',
  148. 'photophobia_onset': 'Photophobia',
  149. 'ataxia_onset': 'Ataxia',
  150. 'hypermetric_saccades_onset': 'Hypermetric saccades',
  151. 'saccadic_hypormetria__onset': 'Saccadic hypometria ',
  152. 'overshoot_onset': 'Overshoot',
  153. 'scanned_speech_onset': 'Scanned speech',
  154. 'dysmetria_onset': 'Dysmetria',
  155. 'hypermetria_onset': 'Hypermetria',
  156. 'abnormal_finger_to_nose_onset': 'Abnormal finger to nose',
  157. 'abnormal_heel_to_shin_onset': 'Abnormal heel to shin',
  158. 'positive_or_abnormal_Romberg_sign_onset': 'Abnormal Romberg sign',
  159. 'square_wave_jerks_onset': 'Square wave jerks',
  160. 'nystagmus_onset': 'Nystagmus',
  161. 'dysdiadochokinesis_onset': 'Dysdiadochokinesis',
  162. 'unable_to_walk_a_line_onset': 'Unable to walk a line',
  163. 'unable_to_perform_tandem_gait_onset': 'Unable to perform tandem gait',
  164. 'involuntary_movement_onset': 'Involuntary movement',
  165. 'chorea_writhing_onset': 'Chorea writhing',
  166. 'athetosis_onset': 'Athetosis',
  167. 'dyskinesia_onset': 'Dyskinesia',
  168. 'hemifacial_spasm_onset': 'Hemifacial spasm',
  169. 'myokimia_onset': 'Myokimia',
  170. 'shaking_onset': 'Shaking',
  171. 'tremor_onset': 'Tremor',
  172. 'tremor_at_rest_onset': 'Tremor at rest',
  173. 'postural_tremor_onset': 'Postural tremor',
  174. 'kinetic_tremor_onset': 'Kinetic tremor',
  175. 'essential_tremor__ET__onset': 'Essential tremor et ',
  176. 'jaw_chin_tremor_onset': 'Jaw chin tremor',
  177. 'myoclonus_onset': 'Myoclonus',
  178. 'cortical_myoclonus_onset': 'Cortical myoclonus',
  179. 'limb_myoclonus_onset': 'Limb myoclonus',
  180. 'facial_myoclonus_onset': 'Facial myoclonus',
  181. 'finger_myoclonus_onset': 'Finger myoclonus',
  182. 'polyminimyoclonus_onset': 'Polyminimyoclonus',
  183. 'dystonia_onset': 'Dystonia',
  184. 'antecollis_onset': 'Antecollis',
  185. 'retrocollis_onset': 'Retrocollis',
  186. 'clenched_fist_onset': 'Clenched fist',
  187. 'hand_dystonia_onset': 'Hand dystonia',
  188. 'foot_dystonia_onset': 'Foot dystonia',
  189. 'upper_motor_neuron__UMN__signs_onset': 'Upper motor neuron umn signs',
  190. 'pseudobulbar_palsy_onset': 'Pseudobulbar palsy',
  191. 'inappropriate_pathological_laughter_onset': 'Inappropriate pathological laughter',
  192. 'inappropriate_pathological_crying_onset': 'Inappropriate pathological crying',
  193. 'hyperreflexia_onset': 'Hyperreflexia',
  194. 'positive_Hoffmann_sign_reflex_onset': 'Positive hoffmann sign reflex',
  195. 'positive_extensor_upgoing__not_absent_flexor_downgoing__Babinski_sign_reflex_onset': 'Babinski sign',
  196. 'positive_extensor_upgoing__not_absent_flexor_downgoing__plantar_reflex_onset': 'Abnormal plantar reflex',
  197. 'spasticity_onset': 'Spasticity',
  198. 'lower_motor_neuron__LMN__signs_onset': 'Lower motor neuron lmn signs',
  199. 'fasciculations_onset': 'Fasciculations',
  200. 'tongue_atrophy_onset': 'Tongue atrophy',
  201. 'dysarthria_onset': 'Dysarthria',
  202. 'dysphasia_onset': 'Dysphasia',
  203. 'swallowing_difficulty_onset': 'Swallowing difficulty',
  204. 'aspiration_onset': 'Aspiration',
  205. 'PEG_feeding_tube_inserstion_onset': 'PEG/feeding tube insertion',
  206. 'stridor_onset': 'Stridor',
  207. 'lightheaded_dizziness_onset': 'Lightheadedness dizziness',
  208. 'orthostatic_hypotension_onset': 'Orthostatic hypotension',
  209. 'urinary_dysfunction_onset': 'Urinary dysfunction',
  210. 'urinary_incontinence_onset': 'Urinary incontinence',
  211. 'urinary_catheter_onset': 'Urinary catheter',
  212. 'urinary_tract_infection__UTI__onset': 'Urinary tract infection (UTI) ',
  213. 'erectile_dysfunction__ED__onset': 'Erectile dysfunction (ED)',
  214. 'abnormal_sweat_onset': 'Abnormal sweat',
  215. 'cold_discolored_hands_feet_onset': 'Cold discolored hands feet',
  216. 'improvement_with_l_dopa__levodopa_or_simenet_onset': 'L-dopa responsiveness',
  217. 'Sex_M': 'Sex (male=1, female=0)',
  218. 'FHx_Yes': 'FHx (yes=1, no=0)',
  219. 'FHx_adopted': 'FHx (adopted=1)'
  220. }
  222. filename = os.path.basename(input_path).split('.')[0]
  223. save_dir = f'{root}/results/{filename}'
  224. os.makedirs(save_dir, exist_ok=True)
  226. weight_path = f'{root}/weights/catboost_model_{yr_th}_yr.cbm'
  227. model_loaded = CatBoostClassifier(iterations=1000, learning_rate=0.1, depth=6, verbose=False)
  228. model_loaded.load_model(weight_path)
  230. # Load and preprocess input
  231. input_data = pd.read_excel(input_path, index_col='index').sort_index()
  232. input_data.index = rename_dict.keys()
  233. X_case = input_data['onset'].to_frame().T.fillna(50)
  234. X_pool = Pool(X_case, feature_names=list(X_case.columns))
  236. # Calculate SHAP values
  237. shap_values = model_loaded.get_feature_importance(X_pool, type="ShapValues")
  238. # pred_th = model_loaded.predict_proba(input_data['onset'])
  239. pred_th = model_loaded.predict_proba(input_data['onset'].fillna(50))
  240. indices_desc = sorted(range(len(pred_th)), key=lambda i: pred_th[i], reverse=True)
  241. sample_index = 0
  243. for class_index in indices_desc:
  244. print(int_dict[class_index], f'Prob:{pred_th[class_index]:.02f}')
  245. shap_values_sample = shap_values[sample_index, class_index, :-1]
  246. base_value = shap_values[sample_index, class_index, -1]
  248. # Force Plot visualization
  249. force_plot = shap.force_plot(
  250. base_value,
  251. shap_values_sample,
  252. X_case.iloc[sample_index, :].round(1),
  253. feature_names=list(rename_dict.values()),
  254. )
  255. display(force_plot)
  256. # Save Force Plot as HTML
  257. prob_str = f"{pred_th[class_index]:.02f}".replace('.', '')
  258. shap.save_html(f"{save_dir}/Prob_{prob_str}_{int_dict[class_index]}.html", force_plot)
  260. if __name__ == '__main__':
  261. root = "path_to_root" # Replace with the actual root path
  262. input_path = "path_to_input.xlsx" # Replace with the actual input path
  263. main(root, input_path, yr_th=3)

chronognosis.py at commit bdac5b4, under Apache-2.0 · at the source

Overview

Authors: Daisuke Ono1,2,3, Hiroaki Sekiya1, Alexia R Maier1, Neill R Graff‐Radford4, Zbigniew K Wszolek4, Dennis W Dickson1
ORCID iDs: Daisuke Ono, Hiroaki Sekiya, Dennis W Dickson
  1. Department of Neuroscience, Mayo Clinic, Jacksonville, FL
  2. Department of Neurology and Neurological Science, Institute of Science – Tokyo, Tokyo, Japan
  3. School of Statistical Thinking, The Institute of Statistical Mathematics, Tokyo, Japan
  4. Department of Neurology, Mayo Clinic, Jacksonville, FL
Institutions: Mayo Clinic (United States); The Institute of Statistical Mathematics (Japan); Mayo Clinic in Florida (United States); Institute of Science Tokyo (Japan)
Journal: Annals of neurology, volume 99, issue 6, pages 1405-1414
Dates: received 6 September 2025; accepted 16 February 2026; published online 14 March 2026; in print June 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1002/ana.78193 · PMID 41830446 · PMCID PMC13206486 · OpenAlex W7135391434
Open access: hybrid, a free copy (OpenAlex)
Status: code verified
Categories: histology / microscopy (modality), human (organism), Alzheimer's / dementia (population), Parkinson's (population), clinical / translational (subfield)
Methods: Machine learning, Statistics
MeSH: Algorithms*, Brain*, Machine Learning*, Parkinsonian Disorders*, Aged, Aged, 80 and over, Female, Humans, Male, Middle Aged, Prediction Algorithms, Predictive Learning Models (* major topic)
Topic: Parkinson's Disease Mechanisms and Treatments (Neurology, Medicine), according to OpenAlex
Funding: JST BOOST Program Japan (JPMJBY24B8); State of Florida Ed; Ethel Moore Alzheimer's Disease
Citations: not cited yet (Europe PMC); 46 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Repository

Its files are read in the Code ↔ Paper reader above, with 2 matches between paragraphs and lines of code.

onnonuro/chronognosis

License: Apache-2.0
State: the link answers, verified on 30 September 2026
Evidence: files inventoried
Commit: bdac5b43a9f05aff514960dab6b12959c7aaddf7, 6 January 2026
Languages: Python (3), Jupyter (1)
Size: 22 files, 4 scripts
Software Heritage: not archived
Found in: the text, “Developing Machine Learning‐Based Prediction Mod”
Holds: README, license file, environment (requirements.txt, setup.py), 1 notebook
Not found: CITATION.cff, tests, continuous integration, documentation
Tools: SHAP (2 files), pandas (1 file)
Availability: 1 check, the latest on 30 September 2026: the link answers
  • 30 September 2026: the link answers
6 files
At the source: github.com/onnonuro/chronognosis

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 4 scripts, each with its path and the digest of its content;
  • 2 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Data availability statement

The paper has a data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

  • it says that the data are available on request

Read it in the paper: doi.org/10.1002/ana.78193.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 6 authors, 12 MeSH terms, 3 funders, 45 references.

Cite

This paper

Ono, D., Sekiya, H., Maier, A. R., Graff‐Radford, N. R., Wszolek, Z. K., & Dickson, D. W. (2026). Chronological Diagnostic Algorithm Predicting Neuropathology in Parkinsonism. Annals of neurology, 99(6), 1405-1414. https://doi.org/10.1002/ana.78193

BibTeX

@article{ono2026chronological,
author = {Ono, Daisuke and Sekiya, Hiroaki and Maier, Alexia R and Graff‐Radford, Neill R and Wszolek, Zbigniew K and Dickson, Dennis W},
title = {{Chronological Diagnostic Algorithm Predicting Neuropathology in Parkinsonism}},
journal = {Annals of neurology},
year = {2026},
month = mar,
volume = {99},
number = {6},
pages = {1405--1414},
publisher = {Wiley},
issn = {0364-5134},
doi = {10.1002/ana.78193},
url = {https://doi.org/10.1002/ana.78193},
pmid = {41830446},
pmcid = {PMC13206486}
}

RIS

TY - JOUR
AU - Ono, Daisuke
AU - Sekiya, Hiroaki
AU - Maier, Alexia R
AU - Graff‐Radford, Neill R
AU - Wszolek, Zbigniew K
AU - Dickson, Dennis W
TI - Chronological Diagnostic Algorithm Predicting Neuropathology in Parkinsonism
T2 - Annals of neurology
J2 - Ann Neurol
PY - 2026
DA - 2026/03/14
VL - 99
IS - 6
SP - 1405
EP - 1414
SN - 0364-5134
PB - Wiley
DO - 10.1002/ana.78193
UR - https://doi.org/10.1002/ana.78193
LA - en
ER -

CSL-JSON

{
"id": "10.1002/ana.78193",
"type": "article-journal",
"title": "Chronological Diagnostic Algorithm Predicting Neuropathology in Parkinsonism",
"container-title": "Annals of neurology",
"author": [
{
"family": "Ono",
"given": "Daisuke"
},
{
"family": "Sekiya",
"given": "Hiroaki"
},
{
"family": "Maier",
"given": "Alexia R"
},
{
"family": "Graff‐Radford",
"given": "Neill R"
},
{
"family": "Wszolek",
"given": "Zbigniew K"
},
{
"family": "Dickson",
"given": "Dennis W"
}
],
"container-title-short": "Ann Neurol",
"volume": "99",
"issue": "6",
"page": "1405-1414",
"DOI": "10.1002/ana.78193",
"PMID": "41830446",
"PMCID": "PMC13206486",
"ISSN": "0364-5134",
"publisher": "Wiley",
"URL": "https://doi.org/10.1002/ana.78193",
"language": "en",
"issued": {
"date-parts": [
[
2026,
3,
14
]
]
}
}

The tracing map gets a citation of its own once an author has validated it and it has a DOI.

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[8] doi:10.1093/braincomms/fcag326 [code]
Brain multiomic profiling identifies tau-related transcriptomic dysregulation in Alzheimer's disease.
Journal: Brain communications
In common: Alzheimer's / dementia, author Dennis W Dickson
[9] doi:10.1002/mds.70355 [code]
Gray Matter Microstructure Measured Using Diffusion Imaging as a Biomarker of Severity in Lewy Body Diseases.
Journal: Movement disorders : official journal of the Movement Disorder Society
In common: pandas, Parkinson's, Alzheimer's / dementia, clinical / translational, 2 references
[10] doi:10.1093/braincomms/fcag257 [code]
Neuroplasticity and immune system are related to altered grey matter networks: a cohort study in sporadic Alzheimer's disease.
Journal: Brain communications
In common: Alzheimer's / dementia, 3 references

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