CN109561821A - Dioptric optical value forecasting system, dioptric optical value prediction technique and program - Google Patents
Dioptric optical value forecasting system, dioptric optical value prediction technique and program Download PDFInfo
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- CN109561821A CN109561821A CN201780031998.3A CN201780031998A CN109561821A CN 109561821 A CN109561821 A CN 109561821A CN 201780031998 A CN201780031998 A CN 201780031998A CN 109561821 A CN109561821 A CN 109561821A
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- age
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
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- G—PHYSICS
- G02—OPTICS
- G02C—SPECTACLES; SUNGLASSES OR GOGGLES INSOFAR AS THEY HAVE THE SAME FEATURES AS SPECTACLES; CONTACT LENSES
- G02C13/00—Assembling; Repairing; Cleaning
Abstract
In order to realize the purpose for quantitatively predicting the following dioptric optical value, dioptric optical value forecasting system (1) includes: input unit (2), for inputting Db (current dioptric optical value), Age (age), Sex (gender) and RL (right/left eyeball)；Computing device (3), for the dioptric optical value (Da) based on Db (current dioptric optical value) and Age (age) prediction after interval (time) passes through；Storage device (4), for storing the predictor formula and tabular value of the following dioptric optical value；And output device (5), for exporting the dioptric optical value of prediction and the dioptric optical value output based on prediction is used for the dioptric optical value of the glasses of recommendation.Da=β 0+ β 1Age+ β 2Age2+β3Age3+β4Age4+β5Db+β6Sex+β7RL。
Description
Technical field
The present invention relates to dioptric optical value forecasting system, dioptric optical value prediction technique and programs.
Background technique
When the axis oculi of given people is extremely long, myopia incidentally occurs.Undergo the retina of the eyeball of axial tension
Position is fallen in except " normal " focal plane.Therefore, the imaging point of distant objects is located at the front of retina, rather than is located at view
In film surface.
Myopia/long sight/astigmatism strength levels are indicated by diopter (lenticular degree) value.Diopter is lenticular
The unit (being indicated with D) of refractive power.Minus sign indicates (- D) instruction myopia.Plus sige indicates that (+D) indicates long sight.Twenty-twenty vision and ± 0
It is corresponding.
Patent document (1) discloses a kind of method for slowing down patient's myopia or long sight progress.According to public in patent document (1)
The method opened, one or more eye parameters of the oculist based on patient, patient are to one or more of first group of haptic lens
A response or both selects one or more haptic lenses from second group of haptic lens, to mention with by first group of haptic lens
The benefit of confession is compared, and provides improved clinical benefit for patient.
In non-patent literature (1), the result of study of study group is reported on the JAMA ophthalmology magazine on April 2nd, 2015.
The group is mainly by the member composition of ophthalmology institute, Ohio State Univ-Columbus USA.About the prediction of myopia progression, this study group
Hypothesis based on 13 candidate risk factors is with high probability constriction risk factors.Test result shows the morning in eyesight testing
The low long sight of stage phase discovery or high myopic refractive be not just by the risk always with the subsequent myopia progression found in ophthalmology test
Increase related.
[reference listing]
[patent document]
[PTL 1]JP 2013-501963 A
[non-patent literature]
[NPL 1] " Prediction of Juvenile-Onset Myopia ", [online], [5 daily test January in 2016
Rope], internet<URL:https: //www.mededge.jp/a/drge/12101>
Summary of the invention
[technical problem]
But above-mentioned conventional method is only configured to measure current dioptric optical value and selects optimum glasses to prescribe.But
Be, using these methods can not quantitative forecast dioptric optical value change in future.
Therefore, it is an object of the present invention to provide the dioptric optical values for capableing of quantitative forecast future dioptric optical value to predict system
System, dioptric optical value prediction technique and program.
[way to solve the problem]
To solve the above-mentioned problems, dioptric optical value forecasting system according to the present invention includes: input unit, is worked as inputting
Preceding dioptric optical value (Db) and age (Age)；And computing device, for pre- based on dioptric optical value (Db) and age (Age) input
Survey the dioptric optical value (Da) after time interval process.
Other component parts of the invention will be described in " specific embodiment ".
[advantageous effect of the invention]
The present invention provides can be with the dioptric optical value forecasting system of quantitative forecast future dioptric optical value, dioptric optical value prediction side
Method and program.
Detailed description of the invention
Fig. 1 is the block diagram for showing the arrangement of dioptric optical value forecasting system according to an embodiment of the invention.
Fig. 2 be show the data obtained by dioptric optical value forecasting system according to an embodiment of the present invention distribution it is (and right
The regression curve answered) figure.
Fig. 3 be show the data obtained by dioptric optical value forecasting system according to an embodiment of the present invention distribution it is (and right
The regression curve answered) figure.
Fig. 4 is the flow chart for showing the embodiment of the present invention and obtaining the processing of dioptric optical value prediction by it.
Specific embodiment
Below with reference to the accompanying drawings detailed description of the present invention embodiment.
(embodiment)
Fig. 1 is the block diagram for showing the arrangement of dioptric optical value forecasting system according to an embodiment of the invention.
It is used to predict following dioptric optical value according to the dioptric optical value forecasting system and method for this embodiment.
As shown in figure (1), dioptric optical value forecasting system (1) includes input unit (2), computing device (3), storage device
(4) and output device (5).Input unit (2), computing device (3), storage device (4) and output device (5) are by for example including hard
The computer of part is realized.Input unit (2) may, for example, be input interface, and including user's operation on printing device etc. with
And the collection from exterior storage medium, communication line and network to data.Output device (5) is, for example, output interface, including all
Such as the display unit of computer monitor, printer etc, write-in to exterior storage medium, and to the defeated of communication line
Out.
Computing device (3) is made of for example following item: central processing unit (CPU)；And special circuit.Storage device
(4) it is made of the storage medium of for example following item: random access memory (RAM)；Read-only memory (ROM)；Hard disk drive
(HDD)；AndMemory.Computing device (3) is executed by the program of the CPU of the computer including its control unit
Processing is to realize.Including storage unit storage in a computer for realizing computer function based on the order from CPU
Program (including dioptric optical value Prediction program).This realizes the cooperation between software and hardware.
There are four inputs for input unit (2) tool: Db (current dioptric optical value), Age (age), Sex (gender) and RL (right side/
Left eye ball).
Computing device (3) is based on current dioptric optical value (Db) and age (Age) prediction after super-interval (time)
Dioptric optical value (Da).Specifically, computing device (3) uses (Db) and (Age) as variable according to the following dioptric optical value
Predictor formula (mathematical formulae (4): (multinomial at the age in claim 2) or mathematical formulae (5) (being described later on)) is directed to
Predict (Da) in each interval.More specifically, computing device (3) use Db, Age, Sex (gender), RL (right/left eyeball) as
Variable predicts Da for each interval according to the multinomial at above-mentioned age.
Storage device (4) storage: the predictor formula (mathematical formulae (4) or mathematical formulae (5)) of the following dioptric optical value；And
For the predictor formula (tabular value of mathematical formulae (4) or mathematical formulae (5) (for example, see [table 4] (being described later on)).
Output device (5) output: pre- by the predictor formula (mathematical formulae (4) or mathematical formulae (5)) of the following dioptric optical value
The dioptric optical value of survey；And the dioptric optical value output also based on prediction is for the glasses of recommendation or the dioptric optical value of haptic lens.
Dioptric optical value forecasting system (1) is described below in detail.
The variation of dioptric optical value after considering prediction 5 years.Prepare 5 years interval datas.Interval data includes within 5 years
595389 entries (116549 personal records).One entry is indicated by the mathematical formulae (1) provided as follows.
ID, RL, Age, Sex, Db, Da (1)
Wherein
ID: for personal identifier
RL: corresponding with right/left 1/2
Sex: corresponding with male/female 1/2
Age: current age
Db: current dioptric optical value
Da: the dioptric optical value after predetermined period (5 years).
The present inventor, which draws attention to the fact that, introduces spline function (the smooth interpolation letter of junction point for the age
Number) bring significantly improving for precision.In addition, introducing spline function for (Db) also brings significantly improving for precision.
Fig. 2 and Fig. 3 show the figures of spline function.
Fig. 2 is the figure for showing data distribution (and corresponding regression curve).Horizontal axis indicates " current age " (Age), the longitudinal axis
It indicates " the current dioptric optical value of dioptric optical value-after 5 years " ((Da)-(Db)).
Fig. 2 shows myopia to rapidly develop in adolescence, and long sight gradually develops at advanced age.
Fig. 3 is the figure for showing data distribution (and corresponding regression curve).Horizontal axis indicates " current dioptric optical value " (Db), indulges
Axis indicates " dioptric optical value after 5 years " (Da) (for convenience's sake, adding a constant to Da in Fig. 3).
Fig. 3 shows linear-nearly constant slope of curve, this instruction variation is not dependent on " current dioptric optical value ".
Therefore, for time series, variation is stable.
Prediction is described below.Two-dimensional spline is considered as preferred prediction model.But, it is contemplated that cost is calculated, it is more real
Model is one-dimensional batten, provides the predicted value provided by mathematical formulae (2).
Da=-0.4112653+0.9871306Db+s (Age)+0.0288855Sex+0.0032082RL
(2)
Wherein s (Age): the spline function at age.
The coefficient of Db is approximately 1.This model is nonlinear relative to the age, and compared with linear model, can
Bring 10.8% raising in terms of mean square error.Compared with dioptric optical value keeps constant 5 years hypothesis, this model is real
The reduction of 42.5% prediction error is showed.The confidence interval of this prediction is of approximately 2 dioptric optical value range.
[the dioptric optical value prediction after given year]
The prediction of dioptric optical value after given year is described below.Set of source data includes 125679 entries, time
Interval was more than 5 years.Since some dioptric optical values are in multiple point in time measurement, can estimate from 5 years interval datas
The data at shorter time interval.
By with mathematical formulae (1) the case where it is identical in a manner of prepare data.One entry is given by following mathematical formulae (3)
Out:
ID, RL, Sex, Age-1 ... ..., Age-n, D1 ..., Dn (3)
Wherein
Age-n:n years old age；And
Dioptric optical value when Dn:n years old age.
In mathematical formulae (3), an entry has n dioptric optical value, thus have n (n-1)/2 year interval.What year was spaced
Quantity is very big.The quantity of overall data point is 3930164.
[table 1] shows the counting at corresponding each year interval.
[table 1]
| Interval | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
| It counts | 35367 | 26344 | 95152 | 13194 | 85118 | 82366 | 44066 | 45292 | 61572 | 6807 | 4886 |
Zero year interval data (that is, age-grade multiple dioptric optical values) are excluded from overall data.That is, between the year used
Every the quantity of data point be 3930164-35367=3894797.
Using the data by mathematical formulae (3) and [table 1] instruction, model can be created with the dioptric after predicting 1 to 10 year
Angle value.
These models are used for by mathematical formulae (2) and mathematical formulae (4) given below
The polynomial regression about the age indicated is tested.
Da=β 0+ β 1Age+ β 2Age2+…+βiAgei+β5Db+β6Sex+β7RL (4)
Wherein i: integer of the range from 2 to 5.
[table 2] shows the result obtained by these models.
[table 2]
| Interval | Db | S | R_by_s | 2 | 3 | 4 | R_by_4 | 5 |
| 1 | 0.08930 | 0.08051 | 0.09843 | 0.08200 | 0.08135 | 0.08105 | 0.09246 | 0.08083 |
| 2 | 0.14499 | 0.11735 | 0.24036 | 0.12059 | 0.11856 | 0.11790 | 0.23563 | 0.11767 |
| 3 | 0.21529 | 0.15860 | 0.26331 | 0.16364 | 0.16034 | 0.15938 | 0.25973 | 0.15925 |
| 4 | 0.40754 | 0.21159 | 0.48081 | 0.22120 | 0.21461 | 0.21268 | 0.47813 | 0.21259 |
| 5 | 0.50278 | 0.28964 | 0.42392 | 0.30959 | 0.29530 | 0.29175 | 0.41972 | 0.29163 |
| 6 | 0.59421 | 0.31831 | 0.46432 | 0.33660 | 0.32510 | 0.32080 | 0.46012 | 0.31906 |
| 7 | 0.65789 | 0.33723 | 0.48740 | 0.35367 | 0.34036 | 0.33804 | 0.48639 | 0.33790 |
| 8 | 0.77591 | 0.40230 | 0.48151 | 0.42143 | 0.40706 | 0.40350 | 0.47996 | 0.40307 |
| 9 | 0.86388 | 0.44090 | 0.48963 | 0.45913 | 0.44695 | 0.44381 | 0.48626 | 0.44298 |
| 10 | 0.93886 | 0.47646 | 0.49251 | 0.49598 | 0.48446 | 0.48228 | 0.48632 | 0.48253 |
Wherein:
Interval: the year interval between dioptric optical value measurement twice；
Db: the root-mean-square error when Db (dioptric optical value earlier) is the amount of the prediction of Da (subsequent dioptric optical value)
(RMSE) estimated value, (hereinafter referred to as E_b)；
S: the estimated value (hereinafter referred to as E_s) of the RMSE of the amount of the prediction of the Da of the s (spline function) for the age is used；
R_by_s:(E_b-E_s)/E_b (corresponds to the pass the error slip obtained using the spline function at age)；
2: by using the estimated value of the RMSE of the amount of the prediction of the Da of the quadratic function acquisition at age；
3: by using the estimated value of the RMSE of the amount of the prediction of the Da of the cubic function acquisition at age；
4: by using estimated value (the hereinafter referred to as E_ of the RMSE of the amount of the prediction of the Da of the biquadratic function acquisition at age
4)；
R_by_4:(E_b-E_4)/E_b (corresponds to the pass the error slip obtained using the biquadratic function at age),
5: by using the estimated value of the RMSE of the premeasuring of the Da of five functions acquisition at age.
With reference in [table 2] as a result, the R_by_s (that is, error slip) of the prediction based on spline regression was in >=4 years
Reach 40% to 50% in interval.
In addition, polynomial regression is slightly worse than spline regression for prediction.But the difference between them is small.It is practical
On, the error slip " R_ based on spline regression is no better than based on the error slip " R_by_4 " that quartic polynomial returns
by_s".Difference between them is generally less than 1%.
The estimated value of error as polynomial regression, the comparison between (2), (3), (4) and (5) show estimating in (5)
Evaluation is generally minimum.But the estimated value in 10 years intervals in (4) is minimum.In addition, because of model simplicity between (4) and (5)
And the difference of error reduction is less than the difference of model simplicity and error reduction between (2) to (4), so the present inventor
It draws a conclusion, (4) are preferred.
In general, higher order polynomial brings lesser error.Thus, it appears that it is preferred for selecting the multinomial of higher order
's.But for following reasons, quartic polynomial is preferred for practical application.It is possible, firstly, to pass through simple calculator
Calculate quartic polynomial.Secondly, quartic polynomial, which is returned, is reduced to satisfactory level for error.
95% confidence interval that value instruction passes through the prediction of quartic polynomial shown in [table 3].
[table 3]
| Interval | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
| ± | 0.569 | 0.687 | 0.798 | 0.922 | 1.080 | 1.133 | 1.163 | 1.270 | 1.332 | 1.389 |
[predictor formula of the following dioptric optical value]
The general mathematical formulae (5) that the predictor formula (multinomial at age) of the following dioptric optical value is given by indicates.
But it is noted that table 4 provides coefficient.The prediction mathematical formulae (5) of dioptric optical value is the biquadratic function at age, this is by this hair
Bright inventor is first public.
Da=β 0+ β 1Age+ β 2Age2+β3Age3+β4Age4+β5Db+β6Sex+β7RL (5)
Wherein:
Da: the dioptric optical value after predetermined period,
β n: coefficient is derived from the value indicated in table by corresponding age and polynomial corresponding entry,
Age: current age,
Db: current dioptric optical value,
Sex: corresponding with male/female 1/2, and
RL: corresponding with right/left 1/2.
[table 4]
| Interval | β0 | β1 | β2 | β3 | β4 | β5 | β6 | β7 |
| 1 | -0.1039 | 45.31 | -30.39 | 25.55 | -16.86 | 0.9923 | 0.006172 | 0.0005589 |
| 2 | -0.1708 | 70.47 | -44.20 | 34.86 | -21.27 | 0.9915 | 0.01307 | 0.001559 |
| 3 | -0.2472 | 92.72 | -54.93 | 41.71 | -24.78 | 0.9897 | 0.02352 | 0.001904 |
| 4 | -0.3310 | 125.2 | -74.74 | 57.00 | -33.65 | 0.9881 | 0.03028 | 0.002851 |
| 5 | -0.4168 | 215.4 | -130.9 | 98.12 | -56.85 | 0.9855 | 0.02969 | 0.003241 |
| 6 | -0.5144 | 168.7 | -99.11 | 67.70 | -31.18 | 0.9820 | 0.03705 | 0.003673 |
| 7 | -0.5740 | 149.1 | -83.24 | 53.88 | -23.32 | 0.9809 | 0.04835 | 0.004822 |
| 8 | -0.6308 | 131.0 | -70.12 | 46.84 | -21.30 | 0.9777 | 0.04836 | 0.005165 |
| 9 | -0.7104 | 108.4 | -56.59 | 38.47 | -18.37 | 0.9745 | 0.06114 | 0.005588 |
| 10 | -0.7559 | 74.36 | -39.26 | 25.04 | -12.10 | 0.9753 | 0.07797 | 0.002963 |
The operation of dioptric optical value forecasting system (1) with above-mentioned arrangement is described below.
Fig. 4 is the flow chart for showing the dioptric optical value prediction carried out by dioptric optical value forecasting system (1).For example, as meter
The CPU for calculating a part of device (3) executes this process.
Firstly, in step sl, input unit (2) input Db (current dioptric optical value), Age (age), Sex (gender) and
RL (right/left eyeball).Input unit (2) for example, the user's operation etc. on printing device；And from exterior storage medium or
Collection of the communication line to Db (current dioptric optical value) and Age (age) data.
Next, in step s 2, computing device (3) reads the following dioptric optical value being stored in storage device (4)
Predictor formula (mathematical formulae (5)) and tabular value ([table 4]).
Next, in step s3, computing device (3) use Db, Age, Sex (gender) and RL (right/left eyeball) as
Variable carrys out the dioptric optical value according to the multinomial (mathematical formulae (5)) at age for each interval prediction after interval is passed through
(Da)。
Next, in step s 4, the dioptric optical value of output device (5) output prediction, and also based on the dioptric of prediction
Dioptric optical value of the angle value output for the glasses of recommendation.Output device (5) by the dioptric optical value of prediction and be used for recommend glasses
Dioptric optical value be output to such as display unit and printer.Output device (5) includes write-in to exterior storage medium and right
The output of the communication line of such as network etc.
As described above, dioptric optical value forecasting system (1) includes: input unit (2), for inputting according to this embodiment
Db (current dioptric optical value), Age (age), Sex (gender) and RL (right/left eyeball)；Computing device (3), for being based on dioptric
The dioptric optical value (Da) of angle value (Db) and age (Age) prediction after interval (time) passes through；Storage device (4), for depositing
Store up the predictor formula (mathematical formulae (5)) and tabular value ([table 4]) of the following dioptric optical value；And output device (5), it is pre- for exporting
The dioptric optical value of survey, and dioptric optical value of the dioptric optical value output for the glasses of recommendation also based on prediction.
In this embodiment, computing device (3) uses Db, Age, Sex (gender) and RL (right/left eyeball) as variable
To predict Da for each interval according to the predictor formula (mathematical formulae (5)) and tabular value ([table 4]) of the following dioptric optical value.
The dioptric optical value prediction technique used in dioptric optical value forecasting system (1) executes computer: input is when anteflexion
The input step of shading value (Db) and Age (age)；Predictor formula (the mathematics of the following dioptric optical value is read from storage device (3)
Formula (4) or (5)) and tabular value (such as [table 4]) and according to the predictor formula of the following dioptric optical value (mathematical formulae (4) or
(5)) and tabular value (such as [table 4]) is for each calculating step for being spaced prediction (Da).Db, Age, Sex (gender) and RL (right/
Left eye ball) it is used as variable.Calculate Db and Age based on input.Finally, computer executes output step-output prediction dioptric
Angle value, and dioptric optical value of the dioptric optical value output for the glasses of recommendation also based on prediction.
This process makes it possible to predict following dioptric optical value (for example, after 5 years).It can also be defeated according to predicting
Out for the dioptric optical value of glasses to prescribe.Following dioptric optical value of prediction makes it possible to estimate in advance such as following myopia
Etc risk and manage such risk.
The present invention is not limited to the above embodiments, and is included within the scope of the appended claims the spirit of that invention of description
It is interior other to modify and apply.
In addition, dioptric optical value forecasting system and dioptric optical value prediction technique may each comprise by dioptric optical value forecasting system
Separate hardware or software realization computing function.In addition, dioptric optical value forecasting system, dioptric optical value prediction technique, program meter
Calculation and arithmetic processing can be realized by specific integrated circuit (ASIC) etc. rather than computer program.
In addition, information (such as realizing the program of corresponding function, table, file) can be stored in storage equipment.This
Kind storage equipment may include: hard disk or solid state drive (SSD)；Or such as integrated circuit (IC) card, secure digital (SD) card
Or the storage medium of CD etc.In addition, in the present specification, the processing step of documented time Series Processing is not limited to root
Processing is executed with time series approach according to documented order.It further includes the processing that concomitantly or is executed separately (for example, simultaneously
Row processing or the processing of object-oriented).This does not need always to be handled in a manner of time series.
In addition, above-described embodiment uses title " dioptric optical value forecasting system and dioptric optical value prediction technique ".But it uses
This title is for convenience's sake.For example, such as " dioptric optical value prediction meanss " or " dioptric optical value calculating side can be used
The title of method " etc.
The Japanese patent application No.2016-128315's that on June 29th, 2016 submits includes specification, claims
It is incorporated herein by reference in their entirety with the disclosure including attached drawing.
The all publications, patents and patent applications quoted in this specification are incorporated herein by reference in their entirety.
[label list]
1 dioptric optical value forecasting system
2 input units
3 computing devices
4 storage devices
5 output devices
Claims (9)
1. a kind of dioptric optical value forecasting system, comprising:
Input unit, for inputting current dioptric optical value (Db) and age (Age)；
Computing device, for being passed through based on the dioptric optical value (Db) inputted by input unit and age (Age) prediction in time interval
Dioptric optical value (Da) after crossing；And
Output device, for exporting the dioptric optical value (Da) calculated by computing device.
2. dioptric optical value forecasting system as described in claim 1, wherein computing device uses dioptric optical value (Db) and age
(Age) dioptric optical value (Da) is predicted for each interval according to the multinomial at age as variable.
3. dioptric optical value forecasting system as claimed in claim 2, wherein computing device uses dioptric optical value (Db), age
(Age), gender (Sex) and right/left eyeball (RL) are directed to each interval according to the multinomial at age as variable and predict dioptric
Angle value (Da).
4. dioptric optical value forecasting system as claimed in claim 2, comprising:
Storage device, for storing the multinomial at age and for the polynomial tabular value at age.
5. dioptric optical value forecasting system as claimed in claim 2, wherein output device is based on the polynomial prediction by the age
Dioptric optical value export the dioptric optical values of the glasses for recommendation.
6. dioptric optical value forecasting system as claimed in claim 2, wherein the multinomial at age is four letters at age (Age)
Number.
7. dioptric optical value forecasting system as claimed in claim 2, wherein the multinomial at age is by formula table given below
Show:
Da=β 0+ β 1Age+ β 2Age2+β3Age3+β4Age4+β5Db+β6Sex+β7RL
Wherein:
Da: the dioptric optical value after predetermined period,
β n: polynomial each coefficient,
Age: current age,
Db: current dioptric optical value,
Sex: corresponding with male/female 1/2, and
RL: corresponding with right/left 1/2.
8. a kind of dioptric optical value prediction technique, comprising:
Input step inputs current dioptric optical value (Db) and age (Age)；
Step is calculated, based on the dioptric optical value (Db) and age (Age) inputted in input step, prediction is passed through in time interval
Dioptric optical value (Da) later；And
Step is exported, the dioptric optical value (Da) calculated in calculating step is exported.
9. it is a kind of for making computer be used as the program of dioptric optical value forecasting system,
The dioptric optical value forecasting system includes: input unit, for inputting current dioptric optical value (Db) and age (Age)；It calculates
Device, for being predicted after time interval process based on the dioptric optical value (Db) inputted by input unit and age (Age)
Dioptric optical value (Da)；And output device, for exporting the dioptric optical value (Da) calculated by computing device.
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2016-128315 | 2016-06-29 | ||
| JP2016128315A JP6247722B1 (en) | 2016-06-29 | 2016-06-29 | Diopter value prediction system, diopter value prediction method and program |
| PCT/JP2017/023123 WO2018003672A1 (en) | 2016-06-29 | 2017-06-23 | Diopter value predict system, diopter value predict method, and program |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109561821A true CN109561821A (en) | 2019-04-02 |
Family
ID=60659030
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201780031998.3A Pending CN109561821A (en) | 2016-06-29 | 2017-06-23 | Dioptric optical value forecasting system, dioptric optical value prediction technique and program |
Country Status (5)
| Country | Link |
|---|---|
| JP (1) | JP6247722B1 (en) |
| KR (1) | KR20190021210A (en) |
| CN (1) | CN109561821A (en) |
| SG (1) | SG11201809517PA (en) |
| WO (1) | WO2018003672A1 (en) |
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|---|---|---|---|---|
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Also Published As
| Publication number | Publication date |
|---|---|
| WO2018003672A1 (en) | 2018-01-04 |
| JP2018004784A (en) | 2018-01-11 |
| JP6247722B1 (en) | 2017-12-13 |
| KR20190021210A (en) | 2019-03-05 |
| SG11201809517PA (en) | 2018-11-29 |
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