Diagnostic systems and methods with global data center and local autonomous cell

1 . A method for diagnosing diseases in human patients comprising:

providing a set of global data to a global data center, wherein the global data comprises data from a tissue diffractometer;

processing the set of global data and categorizing the processed set of global data into data clusters using a processor coupled to the global data center, wherein each data cluster corresponds to a diagnostic indicator for assessment of a physiological or pathological condition;

measuring a local diffraction data of a local patient using a local tissue diffractometer of a local autonomous cell, wherein the local tissue diffractometer is configured to perform one or both of small angle X-ray scattering (SAXS) measurements, and wide angle X-ray scattering (WAXS) measurements;

communicating the local diffraction data and local patient data from the local autonomous cell to the global data center;

processing the local diffraction data and comparing the processed local diffraction data with the data clusters to determine a local diagnostic indicator for the local patient using the processor; and

communicating the local diagnostic indicator from the global data center to the local autonomous cell.

2 . The method for diagnosing diseases in human patients of claim 1 , wherein the measuring the local diffraction data comprises measuring a sample comprising α-keratin or collagen.

3 . The method for diagnosing diseases in human patients of claim 1 , wherein the measuring the local diffraction data comprises in vivo or in vitro measurement of a sample comprising hair, nail, skin, or tissue of an internal organ.

4 . The method for diagnosing diseases in human patients of claim 1 , wherein the set of global data is provided from a certain geographical region or nation.

5 . The method for diagnosing diseases in human patients of claim 1 , wherein the processor is in the cloud, and uses cloud computing to process data using a distributed network of computers.

6 . The method for diagnosing diseases in human patients of claim 1 , wherein the global data center comprises the processor.

7 . The method for diagnosing diseases in human patients of claim 1 , further comprising an analytical center in communication with the global data center, wherein the analytical center comprises the processor.

8 . The method for diagnosing diseases in human patients of claim 1 , further comprising:

measuring a plurality of local diffraction data of a plurality of local patients using a plurality of local tissue diffractometers of a plurality of local autonomous cells, wherein:

the local diffraction data is one of the plurality of local diffraction data;

the local patient is one of the plurality of local patients;

the local tissue diffractometer is one of the plurality of local tissue diffractometers;

the local autonomous cell is one of the plurality of local autonomous cells; and

a plurality of local patient data is associated with the plurality of local patients;

communicating the plurality of local diffraction data and the plurality of local patient data from the plurality of local autonomous cells to the global data center;

processing the plurality of local diffraction data using the processor;

comparing the plurality of processed local diffraction data with the data clusters to determine a plurality of local diagnostic indicators for the plurality of local patients;

communicating the plurality of local diagnostic indicators from the global data center to the plurality of local autonomous cells.

9 . The method for diagnosing diseases in human patients of claim 8 , wherein local autonomous cells of the plurality of local autonomous cells are in different geographic locations.

10 . The method for diagnosing diseases in human patients of claim 1 , further comprising providing a tissue sample from the local patient to the local autonomous cell to be measured using the local tissue diffractometer.

11 . The method for diagnosing diseases in human patients of claim 10 , wherein the tissue sample comprises one or more of a surgical sample, a resection sample, a pathology sample, or a biopsy sample.

12 . The method for diagnosing diseases in human patients of claim 10 , wherein the tissue sample comprises one or more of hair, nail, skin, or tissue of an internal organ.

13 . The method for diagnosing diseases in human patients of claim 10 , wherein the providing a tissue sample from the local patient to the local autonomous cell comprises the local patient or a medical services provider of the local patient using a user interface to input the local patient data and sending the tissue sample by mail.

14 . The method for diagnosing diseases in human patients of claim 1 , wherein the communicating the local diffraction data and the local patient data from the local autonomous cell to the global data center is done by the local patient or a medical services provider of the local patient using a user interface.

15 . The method for diagnosing diseases in human patients of claim 1 , further comprising communicating the local diagnostic indicator from the local autonomous cell to the local patient or a medical services provider of the local patient using a user interface.

16 . The method for diagnosing diseases in human patients of claim 1 , further comprising encrypting the local diffraction data and the local patient data using a data encryption device coupled to the local tissue diffractometer, wherein the communicating the local diffraction data and the local patient data from the local autonomous cell to the global data center comprises communicating the encrypted local diffraction data and encrypted the local patient data from the local autonomous cell to the global data center.

17 . The method for diagnosing diseases in human patients of claim 1 , wherein the global data center further comprises a global database stored on a central server or in the cloud, wherein the global database comprises the set of global data.

18 . The method for diagnosing diseases in human patients of claim 1 , further comprising depersonalizing the local diffraction data, the local patient data, or any combination thereof before communicating the local diffraction data and the local patient data from the local autonomous cell to the global data center, wherein the communicating the local diffraction data and the local patient data from the local autonomous cell to the global data center comprises communicating the depersonalized local diffraction data and the depersonalized local patient data from the local autonomous cell to the global data center.

19 . The method for diagnosing diseases in human patients of claim 18 , wherein a key for mapping the depersonalized local diffraction data, the local patient data, or any combination thereof is stored in a local institutional database or in an individual personal file of the patient.

20 . The method for diagnosing diseases in human patients of claim 1 , wherein the processing the set of global data and categorizing the processed the set of global data into the data clusters comprises performing a statistical analysis on the processed set of global data.

21 . The method for diagnosing diseases in human patients of claim 1 , wherein the processing the set of global data and categorizing the processed set of global data into the data clusters is done using a machine learning algorithm.

22 . The method for diagnosing diseases in human patients of claim 1 , wherein the local patient data comprises descriptions or data related to symptoms of the local patient comprising one or more of sleep disorders, insomnia, sudden awakenings, somnambulism, apnea, disorders of cerebral circulation, electroencephalogram (EEG) data, sudden convulsions and fainting, headaches and dizziness, and traumatic brain injuries and symptoms thereof.

23 . The method for diagnosing diseases in human patients of claim 1 , wherein the diagnostic indicators relate to one of more of breast cancer, brain cancer, bone cancer, lung cancer, cervical cancer, bladder cancer, head cancer, neck cancer, kidney cancer, intestinal cancer, liver cancer, ovarian cancer, pancreatic cancer, prostate cancer, skin cancer, throat cancer, oral cancer, vaginal cancer, sinus tachycardia of the heart, atrial extra-systoles, ventricular extra-systoles, acute myocardial infarction, heart valve defect, cardiomyopathy, ventricular hypertrophy, heart failure, arrhythmia, atrial fibrillation of the heart, pericarditis, bradycardia of the heart, myocarditis, ischemic stroke, neurological stroke, Alzheimer's disease, glioblastoma, extra-cerebral tumors, bacterial endocarditis (inflammation of the inner lining of the heart), and meningococcal meningitis (inflammation of the membranes of the brain and spinal cord).

24 . The method for diagnosing diseases in human patients of claim 1 , wherein the communicating the local diffraction data and the local patient data from the local autonomous cell to the global data center is done by mail, airmail, courier mail or e-mail.

25 . The method for diagnosing diseases in human patients of claim 1 , wherein the communicating the local diffraction data and the local patient data from the local autonomous cell to the global data center or the communicating the local diagnostic indicator from the global data center to the local autonomous cell occurs about once per day, or about once per week, or about once per month on average.