1. An antenna coil comprising:
a magnetic core;
a substrate wound around the magnetic core;
conductors provided on the substrate;
a receiver coil arranged around the magnetic core and defined by the conductors, the receiver coil being wound so as to be divided into a first receiver coil portion and a second receiver coil portion with a non-coil-wound portion provided therebetween, the second receiver coil portion having an opposite coil winding direction of coil winding to that of the first receiver coil portion; and
a transmitter coil arranged around the magnetic core and defined by the conductors and having a coil axis parallel or substantially parallel to a coil axis of the receiver coil, the transmitter coil being wound so as to be divided into a first transmitter coil portion and a second transmitter coil portion with a non-coil-wound portion therebetween, the second transmitter coil portion having an opposite coil winding direction to that of the first transmitter coil portion; wherein
a region in which the receiver coil is provided and a region in which the transmitter coil is provided at least partially overlap each other when viewed in plan view.
2. The antenna coil according to claim 1, wherein the conductors defining the receiver coil and the conductors defining the transmitter coil are alternately arranged.
3. The antenna coil according to claim 1, wherein the receiver coil and the transmitter coil are provided on the same surface of the substrate.
4. The antenna coil according to claim 1, wherein the receiver coil and the transmitter coil are provided on different surfaces of the substrate.
5. The antenna coil according to claim 1, wherein
the magnetic core includes a bent portion at least at one end thereof in a direction of the coil axes of the receiver coil and the transmitter coil; and
the substrate is wound around a portion of the magnetic core that does not include the bent portion.
6. The antenna coil according to claim 1, wherein the magnetic core is divided into different magnetic core portions, and the first receiver coil portion and the first transmitter coil portion and the second receiver coil portion and the second transmitter coil portion are arranged on the different magnetic core portions.
7. The antenna coil according to claim 1, wherein at least one of a set of the first receiver coil portion and the second receiver coil portion and a set of the first transmitter coil portion and the second transmitter coil portion is connected via a plurality of conductors provided on the substrate.
8. The antenna coil according to claim 1, wherein an electrode film electrically insulated from the conductors is provided on the substrate.
9. The antenna coil according to claim 1, wherein a composite magnetic material composed of resin and magnetic metal is used for the magnetic core.
10. An antenna device comprising:
the antenna coil according to claim 1; and
a circuit substrate on which the antenna coil is mounted.
11. An antenna device comprising:
the antenna coil according to claim 5; and
a circuit substrate on which the antenna coil is mounted; wherein
the bent portion of the magnetic core is arranged along a side surface of the circuit substrate.
12. An antenna device comprising:
the antenna coil according to claim 8; and
a circuit substrate on which the antenna coil is mounted; wherein
a gap is provided between the antenna coil and the circuit substrate; and
a surface of the antenna coil on which the electrode film is provided and the circuit substrate face each other.
13. The antenna coil according to claim 1, wherein the substrate is made of a flexible material.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A computer-based system having a memory and a processor which estimates a patient’s future demand for healthcare services,
the computer-based system comprising a computer-readable instructions that, when executed by the processor, causes the processor to analyze a patient’s drug history, sex, and age, and based on this analysis infers a diagnosis for the patient;
wherein the analysis done by the processor comprises applying at least one rule which defines a relationship among a disease, drug usage expected to be associated with the disease, the sex of a person expected to be associated with the disease, and an age range of a person expected to be associated with the disease; and,
wherein the at least one rule is applied to the patient’s drug history based on a hierarchy of diseases, the hierarchy being a function, at least in part, of a severity of the disease to the patient’s health, and further wherein the hierarchy of diseases is applied such that if the application of the at least one rule yields a plurality of possible diseases including a more severe and a less severe disease, the more severe disease is associated with the patient.
2. The computer-based system of claim 1, wherein the patient’s drug history includes information additionally defining time periods in which a drug was taken or received by a patient.
3. The computer-based system of claim 1, wherein the applied rule includes a span rule, which defines a period of time for which the patient must have been taking a drug for a disease to he associated with the patient.
4. The computer-based system of claim 3, wherein the span rule includes gap rules, which define gaps in the period of time for which a patient must have been taking a drug for a disease to be associated with the patient.
5. The computer-based system of claim 1, wherein the computer further analyzes at least a portion of the patient’s genetic data, and wherein the applied rule includes a genetic rule that specifies a genetic feature of the patient that must be present for the disease to be associated with the patient.
6. The computer-based system of claim 5, wherein the genetic rule is indicative of a predisposition to the disease.
7. The computer-based system of claim 5, wherein the genetic rule is indicative of a predisposition to the disease only when a drug usage is present in a person’s drug history.
8. The computer-based system of claim 1, wherein associating the most severe disease with the patient comprises:
assigning, the disease to the patient based on selecting the highest diagnosis in the hierarchy that is consistent with the applied rule.
9. The computer-based system of claim 1, wherein the patient’s drug history identifies more than one drug taken by the patient, and wherein applying the rule further comprises applying the drug diagnosis rule to the second drug taken by the patient.
10. A computer-implemented method, the method implemented on a computer having at least one processor and a memory, comprising
receiving patient data comprising the patient’s drug history, sex, and age;
analyzing, using the at least one processor of the computer, the patient data, wherein the analysis comprises applying at least one rule which defines a relationship among a disease, drug usage expected to be associated with the disease, the sex of a person to be associated with the disease, and an age range of the person expected to be associated with the disease, and further wherein the at least one rule is applied to the patient’s drug history based on a hierarchy of diseases, the hierarchy being a function, at least in part, of a severity of the disease to the patient’s health, and further wherein the hierarchy of diseases is applied such that if the application of the at least one rule yields a plurality of possible diseases including a more severe and a less severe disease, the more sever disease is associated with the patient; and
based on the analysis, inferring a diagnosis for the patient.
11. The computer-implemented method of claim 10, wherein the patient data additionally includes information additionally defining time periods in which a drug was taken or received by a patient.
12. The computer-implemented method of claim 10, wherein the applied rule includes a span rule, which defines a period of time for which the patient must have been taking a drug for a disease to be associated with the patient.
13. The computer-implemented method of claim 12, wherein the span rule includes gap rules, which define gaps in the period of time for which a patient must have been taking a drug for a disease to be associated with the patient.
14. The computer-implemented method of claim 10, wherein the computer further analyzes at least a portion of the patient’s genetic data, and wherein the applied rule includes a genetic rule that specifies a genetic feature of the patient that must be present for the disease to be associated with the patient.
15. The computer-implemented method of claim 14, wherein the genetic rule is indicative of a predisposition to the disease.
16. The computer-implemented method of claim 14, wherein the genetic rule is indicative of a predisposition to the disease only when a drug usage is present in a person’s drug history.
17. The computer-implemented method of claim 10, wherein associating the most severe disease with the patient comprises:
assigning the disease to the patient based on selecting the highest diagnosis in the hierarchy that is consistent with the applied rule.
18. The computer-implemented method of claim 10, wherein the patient’s drug history identifies more than one drug taken by the patient, and wherein applying the rule further comprises applying the drug diagnosis rule to the second drug taken by the patient.