International Business Machines Corporation

Patent Trials and Appeals Board

Jan 13, 2021

2020002101 (P.T.A.B. Jan. 13, 2021)

UNITED STATES PATENT AND TRADEMARK OFFICE
UNITED STATES DEPARTMENT OF COMMERCE
United States Patent and Trademark Office
Address: COMMISSIONER FOR PATENTS
P.O. Box 1450
Alexandria, Virginia 22313-1450
www.uspto.gov
APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO.
15/279,546 09/29/2016 Corville O. Allen SVL920160130US1 8995
45725 7590 01/13/2021
Walder Intellectual Property Law PC
445 Crestover Circle
Richardson, TX 75080
EXAMINER
OFORI-AWUAH, MAAME
ART UNIT PAPER NUMBER
3629
MAIL DATE DELIVERY MODE
01/13/2021 PAPER
Please find below and/or attached an Office communication concerning this application or proceeding.
The time period for reply, if any, is set in the attached communication.
PTOL-90A (Rev. 04/07)

UNITED STATES PATENT AND TRADEMARK OFFICE
____________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
____________

Ex parte CORVILLE O. ALLEN, ROBERTO DELIMA,
AYSU EZEN CAN, and ROBERT C. SIZEMORE

Appeal 2020-002101
Application 15/279,546
Technology Center 3600
____________

Before JOSEPH A. FISCHETTI, CYNTHIA L. MURPHY, and
AMEE A SHAH, Administrative Patent Judges.

MURPHY, Administrative Patent Judge.

DECISION ON APPEAL
The Appellant1 appeals from the Examiner’s rejection of claims 1–3,
5–13, and 15–22 under 35 U.S.C. § 101. We AFFIRM.2

1 The Appellant is the “applicant” as defined by 37 C.F.R. § 1.42 (e.g., “the
inventor or all of the joint inventors”). “The real party in interest in this
appeal is the following party: International Business Machines
Corporation.” (Appeal Br. 2.)
2 We have jurisdiction under 35 U.S.C. §§ 6(b) and 134(a).
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THE APPELLANT’S INVENTION
According to the Appellant, its invention relates to “an improved data
processing” method (Spec. ¶ 1) which is described in the context of
“electronic medical records (EMRs) for a patient” (id. ¶ 7).
An electronic medical record (EMR) “is a patient information
repository that collects patient data from a variety of sources” (Spec. ¶ 82).
The Appellant is particularly concerned with a portion of patient information
in the electronic record that is conveyed in “a non-standard set of sentences
that are in non-obvious form.” (Id. ¶ 30.) Apparently, such “non-standard
forms of texts” occur in “medical texts and shorthand reports” (id. ¶ 31),
such as the “clinical note section of an electronic medical record” (id. ¶ 17).
The Appellant’s method translates this non-standard-sentence
information into a “verbose” EMR. (Spec. ¶ 66.) “A verbose EMR is an
electronic medical record with parseable sentences generated based on the
hierarchical structure of an unstructured text portion of the EMR.” (Id.)
ILLUSTRATIVE CLAIM
(with our annotations)
1. A method, in a data processing system comprising at least
one processor and at least one memory, the at least one memory
comprising instructions executed by the at least one processor
to cause the at least one processor to implement a clinical
decision support system, the method comprising:
receiving, by the clinical decision support system, a
plurality of patient electronic medical records (EMRs) for a
patient from a plurality of different sources;
for a portion of a patient EMR of the plurality of patient
EMRs, detecting, by an entity recognition component executing
within the clinical decision support system, entities and
analyzing a document structure of the portion of the patient
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EMR to identify a hierarchical structure of the portion of the
patient EMR;
generating, by a document structure analysis component
executing within the clinical decision support system, a
container representation of the portion of the patient EMR
based on the hierarchical structure;
generating, by a knowledge graph drawing component
executing within the clinical decision support system, a
container-based knowledge graph based on the detected entities
and the container representation;
generating, by a sentence generation component
executing within the clinical decision support system, a set of
grammatical representations of one or more relationships
identified within the container representation based on the
container-based knowledge graph and using a set of
predetermined grammatical templates, wherein the set of
grammatical representations comprise natural language
sentences; and
generating, by the clinical decision support system, a
verbose EMR comprising the grammatical representations of
the one or more relationships.
REJECTION
The Examiner rejects claims 1–3, 5–13, and 15–22 under 35 U.S.C.
§ 101 as being directed to a judicial exception (i.e., an abstract idea) without
significantly more. (Final Action 3.) More concisely, the Examiner
concludes that the claims on appeal fail the Alice framework for patent
eligibility.3 We have carefully considered the Appellant’s arguments

3 In Alice Corp. v. CLS Bank Int’l, 573 U.S. 208 (2014), the Supreme Court
provided a two-step framework to detect when an attempt is being made to
patent an abstract idea in isolation. (Id. at 217–18.) In Alice step one, a
determination is made as to whether the claim at issue is “directed to” an
abstract idea. (Id. at 218.) If the claim at issue is “directed to” an abstract
idea, Alice step two must be performed, in which a determination is made as
to whether “additional elements” in the claim, both individually and as an
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regarding the wrongness of this conclusion (see Appeal Br. 5–9, Reply
Br. 2–6), but we are not swayed thereby.
ANALYSIS
The 2019 Revised Patent Subject Matter Eligibility Guidance (“2019
§ 101 Guidance”) provides us with specific steps for discerning whether a
claim satisfies the Alice framework for patent eligibility. (See 2019 Revised
Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50 (Jan. 7, 2019).)4
These steps are “[i]n accordance with judicial precedent” and consist of a
two-pronged Step 2A and a Step 2B. (Id. at 52.)
Step 2A—Prong One
In the first prong of Step 2A (Prong One), we determine whether the
claim “recites” an abstract idea. (2019 § 101 Guidance, 84 Fed. Reg. at 54.)
The Guidance “extracts and synthesizes key concepts identified by the
courts as abstract ideas,” and these concepts include “[m]ental processes,”
that is “concepts performed in the human mind.” (Id. at 52.) For example,
“translating a functional description of a logic circuit into a hardware
component description of the logic circuit” is a “mental process”
constituting an “abstract idea.” (Synopsys, Inc. v. Mentor Graphics Corp.,
839 F.3d 1138, 1139 (Fed. Cir. 2016).)
We agree with the Examiner that independent claim 1 recites
limitations which equate to “a person mentally comparing words or terms to

ordered combination, contribute “significantly more” than the abstract idea.
(Id.)
4 The Manual of Patent Examining Procedure (“MPEP”) now incorporates
this revised guidance and subsequent updates at Section 2106 (9th ed.
Rev. 10.2019, rev. June 2020).
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identify relationships between the terms or words” and “a person looking at
a document and breaking up paragraphs of text or sentences within the
document into sections.” (Final Action 4.) In other words, we agree with
the Examiner that independent claim 1 recites a concept involving the
translation of textual information.
When a medical practitioner uses shorthand for recording diagnosis-
related notes about a patient, it follows that there would be a medical-
vocabulary-proficient person on staff who is responsible for translating these
notes into standard sentences for later readability. This person could be, for
example, charged with translating the “clinical note section of an electronic
medical record” (Spec. ¶ 107) shown in Figure 6A below.

The above drawing is “an example clinical note section of an electronic
medical record.” (See Spec. ¶ 17.) The clinical-note section is “for a given
patient” and includes “words or terms” specific to “vocabularies in the
biomedical sciences.” (Id. ¶ 106.) It also “includes multiple sub-sections,”
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particularly, “a list numbered with roman numerals,” and, more particularly,
subsections I, II, and III. (Id. ¶ 107.)
The medical professional charged with translating the clinical-note
section would be familiar with biomedical-science vocabulary and the
ontology therebetween. (See Spec. ¶ 106). For example, he/she would
recognize that the diagnosis pertains to biopsies at certain breast locations
(i.e., left nodule, left auxiliary nodule, left inferior) and abnormal-cell results
revealed by such biopsies (e.g., ductal carcinoma, invasive, in situ,
Nottingham index, nuclear grade, solid type, intraluminal necrosis).
The medical professional charged with translating the clinical-note
section would be aware of the hierarchical structure created by the
subsections I–III as shown in Figure 6B below.

The above drawing shows a “container representation” of the clinical-note
section of the patient’s EMR. (Id. ¶ 18.) The medical professional charged
with translating the clinical-note section would know that subsections I–III
correspond to the respective biopsy locations. More particularly, this person
would know that subsection I “contains” biopsy information relating to the
left nodule, subsection II “contains” biopsy information relating to the left
axillary nodule, and subsection III “contains” biopsy information relating to
the left inferior. (Id. Fig. 6A; see also Fig. 8.)
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The medical professional charged with translating the above
clinical-note section would generate grammatically correct sentences to
convey its content. The grammatical correctness of this translation would
stem from the person’s grade-school knowledge of parts of speech and
sentence structure (and the graphing thereof). And, the person would apply
this grade-school knowledge to each subsection of the clinical-note section,
as diagrammed for subsection II in Figure 9 below.

The above drawing is “an example parse tree generated from a knowledge
graph.” (Spec. ¶ 21.) The illustrated tree graphs a person’s thought process
when identifying parts of speech and appropriately placing them in a
sentence structure. As multiple sentence structures can sometimes be used
to convey the same content, the medical practice could provide templates of
preferred sentence structures for the sake of uniformity. (See id. ¶ 112.)
Thus, the person responsible for translation of EMR materials in a
medical practice would receive “a plurality of patient electronic medical
records (EMRs) for a patient from a plurality of different sources.” (Appeal
Br., Claims App.) For each clinical-note section of the EMR, this person
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would detect “entities,” analyze “a document structure of the portion of the
patient EMR to identify a hierarchical structure of the portion of the patient
EMR,” generate “a container representation of the portion of the patient
EMR based on the hierarchical structure,” generate “a container-based
knowledge graph based on the detected entities and the container
representation,” generate “a set of grammatical representations” comprising
“natural language sentences,”5 and generate “a verbose EMR.” (Id.)
Consequently, under Prong One of Step 2A, independent claim 1
recites an abstract idea (i.e., the mental process of translating a clinical-note
section of an EMR into grammatically correct sentences), and we proceed to
the second prong of Step 2A.
Step 2A—Prong Two
In the second prong of Step 2A (Prong Two), we evaluate whether the
claim contains additional elements that “integrate” the abstract idea “into a
practical application.” (See 2019 § 101 Guidance, 84 Fed. Reg. at 52.)
“Additional elements” are “claim features, limitations, and/or steps that are
recited in the claim beyond the identified judicial exception.” (Id. at 55,
n.24.) Thus, the “additional elements” in independent claim 1 are those
“beyond” the abstract idea of translating a clinical-note section of an EMR
into grammatically correct sentences.
We agree with the Examiner that the components and the clinical
support system recited in independent claim 1 could constitute additional

5 These grammatical representations would be of “one or more relationships
identified within the container representation,” would be based on “the
container-based knowledge graph,” and would use “a set of predetermined
grammatical templates.” (Appeal Br., Claims App.)
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elements. (See Final Action 4.) We also agree with the Examiner that these
additional elements, individually and in combination, “amount to no more
than mere instructions to apply the exception using a generic computer
component” and/or “generally link[] the abstract idea to a clinical support
system environment.” (Id. at 5.)
As for the components, independent claim 1 requires the detecting
and the first three generating steps to be performed by an entity recognition
component, a document structure analysis component, a knowledge graph
drawing component, and a sentence generation component. (Appeal Br.,
Claims App.) In the context of the claims on appeal, “[a] component may
be, but is not limited to, software, hardware and/or firmware or any
combination thereof that performs the specified functions” and the term
“component” is “not intended to be limiting of any particular
implementation for accomplishing and/or performing the actions, steps,
processes, etc., attributable to and/or performed by the component.” (Spec.
¶ 37.) Thus, the Specification expressly defines these additional elements as
generic computer components that perform EMR-translating functions in a
generic fashion.6
As for the clinical support system, independent claim 1 requires the
components to be executing within the clinical support system; and requires
the receiving step and the final generating step to be performed by the
clinical decision support system. (Appeal Br., Claims App.) This system is
implemented in the processor of a generic data processing system that “may

6 Moreover, as pointed out by the Examiner, because the Specification says
that a component is not limited to software/hardware/firmware, a computer
may not even be involved in the implementation of the recited functions.
(See Final Action 3.)
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take the form of any of a number of different data processing systems
including client computing devices, server computing devices, a tablet
computer, laptop computer, telephone or other communication device, a
personal digital assistant (PDA), or the like.” (Spec. ¶¶ 7, 76, Fig. 2.)
Claim 1 does not specify any coordination between the clinical support
system and the components, and does not specify any details about receipt of
the EMR information and/or generation of the verbose EMR.
Consequently, under Prong Two of Step 2A, the additional elements
in independent claim 1 do not integrate the Appellant’s EMR-translating
method into a practical application, and so we proceed to Step 2B.
Step 2B
In Step 2B, we evaluate whether the additional elements recited in the
claim, individually or in combination, amount to “significantly more” than
the abstract idea itself. (2019 § 101 Guidance, Federal Register Vol. 84,
No. 4, 56.) If the additional elements consist of a conventional arrangement
of well-understood, routine, conventional computer components, they will
not amount to significantly more, and the claim does not satisfy the Alice
framework for patent eligibility. (Id.)
We agree with the Examiner that the additional elements in
independent claim 1 do not “amount to significantly more” than the abstract
idea of translating a clinical-note section of an EMR into grammatically
correct sentences. (Final Action 5.)
As for the components, as discussed above, the Specification defines a
“component” as something that “may be, but is not limited to, software,
hardware and/or firmware or any combination thereof that performs the
specified functions.” (Spec. ¶ 37.) Per this definition, the components listed
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in independent claim 1, would be, at best, conventional computer
components. The Specification’s further disclosure/depiction of the entity
recognition component 520, the document structure analysis component 530,
the knowledge graph drawing component 540, and the sentence generation
component 550 only illuminates the abstract-idea-embedded responsibilities
of these components. (See id. ¶¶ 106–113.) And the Specification is clear
that “any name associated with a particular component is, unless otherwise
specified, for purposes of convenience of reference and not intended to be
limiting to a specific implementation.” (Id. ¶ 37.)
As for the clinical decision support system, the Specification discloses
a cognitive system 300 “that is configured to provide medical treatment
recommendations for patients.” (Spec. ¶ 77.) Inasmuch as the disclosed
cognitive system 300 can be equated to the claimed clinical decision support
system, it is depicted as comprising plural computing devices (see id. Fig. 3)
which are earlier described as “comprising one or more processors and one
or more memories, and potentially any other computing device elements
generally known in the art including buses, storage devices, communication
interfaces, and the like” (id. ¶ 56; see also Fig. 1). Thus, the Specification
describes the system 300 as a conventional computer component.
As for the ordered combination of the additional elements recited in
independent claim 1, Figure 5 diagrams a “mechanism” (Spec. ¶ 16) that
receives an EMR 501, that includes entity recognition component 520, the
document structure analysis component 530, the knowledge graph drawing
component 540, and the sentence generation component 550, and that
generates a verbose EMR 561. (See id. ¶¶ 16, 106–115.) The Specification
defines a “mechanism” as something that may be “an implementation of the
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functions or aspects of the illustrative embodiments in the form of an
apparatus, a procedure, or a computer program product.” (Id. ¶ 35.) “In the
case of a procedure, the procedure is implemented by one or more devices,
apparatus, computers, data processing systems, or the like.” (Id.) “Thus,”
the mechanisms described in the Specification “may be implemented” as
“software executing on general purpose hardware.” (Id.; see also
¶¶ 135–139.)
Additionally or alternatively, the Specification describes and depicts
an “entity relation detection component 120” that seems to collectively
perform the functions of the components 520, 530, 540, and 550, and also
create the verbose EMR. (See Spec. ¶¶ 64–65, Fig. 1.) The Specification
states that “any functionality attributed to a component may be equally
performed by multiple components, incorporated into and/or combined with
the functionality of another component of the same or different type, or
distributed across one or more engines of various configurations.” (Spec.
¶ 37.) Thus, neither the Specification nor the claims require a certain
ordered combination of the recited components.
Consequently, the additional elements in independent claim 1, when
considered individually, and when considered as an ordered combination, do
not add significantly more to the Appellant’s EMR-translating method.
Therefore, we agree with the Examiner that claim 1 recites a judicial
exception without significantly more.
The Appellant’s Arguments
The Appellant argues that “the functions and activities recited in
claim 1” are “functions and activities [] specific to computer-implementation
of a clinical decision support system.” (Appeal Br. 6.) According to the
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Appellant, “[a]s a practical matter, these functions could not be performed
entirely in a human’s mind.” (Id.; see also Reply Br. 2.) However, as
discussed above, a medical professional charged with translating EMR
information could and would detect entities (e.g., biomedical-science terms),
recognize hierarchical subsection representations and the information
respectively contained therein, and follow a template to formulate
grammatically correct sentences.7
The Appellant argues that because claim 1 requires computer
components to perform the recited EMR-translating functions, these
functions cannot be performed in a person’s mind. (See Appeal Br. 6; see
also Reply Br. 2.) However, when an additional element in a claim is a
“computer,” the relevant question is not whether the claim requires the
computer to accomplish a recited function. (Alice, 573 U.S. at 223.) Rather,
“the relevant question” is whether the claim does more than simply “instruct
the practitioner to implement the abstract idea” on a computer. (Id. at 225.)
The mere recitation of a computer in the claim, and/or words simply saying
“apply” the abstract idea “with a computer,” will not transform the abstract
idea into a patent-eligible invention.” (Id. at 223.) In short, the sheer
introduction of a computer into the claim is not enough to “impart patent
eligibility.” (Id.)

7 To the extent that EMR information could theoretically be too complex for
a person to practically translate, independent claim 1 is not confined to EMR
information of such complexity. The container representation shown in
Figure 6B, the section-content tree shown in Figure 8, and the sentence-
structure graph shown in Figure 9 could be practically performed in a
person’s mind, and would part of his/her mental translation of the EMR
information shown in Figure 6A.
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The Appellant argues that the computer components in independent
claim 1 “are not recited at a high level of generality.” (Appeal Br. 7.)
However, claim 1’s receiving, detecting, analyzing, and generating steps
do indeed recite an outcome (i.e., the receipt of EMRs, the detection of
entities, the identification of a hierarchical structure, a container
representation, a container-based knowledge graph, a set of grammatical
representations, and a verbose EMR) with few, if any, software details as to
how this outcome is accomplished. Thus, the computer-implemented steps
in independent claim 1 are claimed in terms of their functionality and, as
discussed above, these functions align with those performed by a person
when translating EMR information in his/her mind.8
The Appellant argues that claimed method addresses, and solves, “a
problem in the software arts.” (Appeal Br. 8.) According to the Appellant,
the problem is that information in EMRs are not “parseable medical
sentences” and biomedical-science words therein are “related across
sentences.” (Id.) And, according to the Appellant, the claimed invention

8 Such a claiming strategy is also susceptible to attack under 35 U.S.C. § 112
if the specification does not disclose “the computer and the algorithm(s) that
achieve the claimed function in sufficient detail that one of ordinary skill in
the art reasonably conclude that the inventor possessed the claimed subject
matter at the time of filing.” (Examining Computer-Implemented Functional
Claim Limitations for Compliance With 35 U.S.C. 112, 94 Fed. Reg. 57, 61
(Jan. 7, 2019.)) This susceptibility was at the forefront in In re Aoyama, 656
F.3d 1293, 1298 (Fed. Cir. 2011) because the illustrated flowchart failed “to
describe, even at a high level, how a computer could be programmed to
produce the structure that provides the results described in the boxes.”
Consequently, the Appellant’s arguments that Aoyama supports its position
that independent claim 1 is directed to a “special purpose computer for
performing the claimed functions” (Appeal Br. 6, see also Reply Br. 2–3)
might create more questions than answers.
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solves this problem “by connecting multiple sentences, drawing a
knowledge graph based on document structure, and generating parseable
natural language sentences that allow for reasoning and conjectures in
decision making.” (Id.) However, this problem has existed for as long as
doctors have been using shorthand and biomedical-science terms to record
information about their patients. And, for just as long, the solution to this
problem has been for a medical-vocabulary-proficient person on staff to
translate this information into readable sentences.
The Appellant argues that the claimed method, like the claimed
method in Enfish LLC v. Microsoft Corp., 822 F.3d 1327 (Fed. Cir. 2016),
“generates computer data structures that improve the manner in which the
computer itself processes information in a patient EMR.” (Appeal Br. 9.)
However, even if the claimed container representation, knowledge graph,
and/or grammatical representations can be called “data structures,” they
mirror the organization of data in a person’s mind when translating a
patient’s medical-record information. (See Spec. Figs. 6B, 8, 9.)
The Appellant argues that, although “it is a trivial matter for the
human mind to identify entity relationships,” the claimed invention is
“directed to an automated approach to entity detection that works across
sentences by drawing a knowledge graph based on document structure.”
(Reply Br. 4.) Insofar as the Appellant is saying that innovative software
programming (e.g., specialized algorithms) is sometimes necessary to
automate trivial mental processes, we do not necessarily disagree. The
trouble is that the Appellant neither discloses nor claims such innovative
software. Rather, the claimed method recites the thought processes
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undertaken by person when translating a patient’s medical record, and tells a
practitioner to apply these thought processes using a computer.9
The Appellant argues that “[t]he functions of the claim are for the
express purpose of improving computerized clinical decision support
systems.” (Reply Br. 5.) This intended use of the EMR-translating steps in
independent claim 1, at most, generally links them to an environment
involving a clinical support system. Even if a claim links a method to a
technological environment, this does not, in and of itself, render the claim
any less abstract. (See 2019 § 101 Guidance, Federal Register Vol. 84,
No. 4, at 55.)10
Consequently, after careful consideration of the Appellant’s
arguments, we still agree with the Examiner that independent claim 1 recites
a judicial exception without significantly more.
Summary
We sustain the Examiner’s rejection of independent claim 1 under
35 U.S.C. § 101. Independent claims 11 and 18 recite corresponding

9 The Appellant asserts that the Examiner’s position “is akin to saying an
automobile is an abstract idea because humans can walk from point A to
point B, even though the entire purpose of the automobile is to eliminate
such human effort.” (Reply Br. 4.) This assertion actually makes our point.
The innovational details involved in developing a machine that can be used
to transport humans from point A to point B is worthy of patent eligibility.
The mere idea of using a machine to transport humans from point A to
point B so they do not have to walk is not.
10 For example, in Elec. Power Grp., LLC v. Alstom S.A., 830 F.3d 1350,
1354 (Fed. Cir. 2016) the Federal Circuit held that “limiting the claims to the
particular technological environment of power-grid monitoring is, without
more, insufficient to transform them into patent-eligible applications of the
abstract idea at their core.”
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receiving, detecting, analyzing, and generating steps, and the Appellant
does not advance any argument beyond the unpersuasive ones discussed
above. As for the dependent claims, they are not argued separately. Thus,
we likewise sustain the Examiner’s rejection of claims 2, 3, 5–13, 15–22
under 35 U.S.C. § 101.
CONCLUSION
Claims
Rejected
35 U.S.C.
§
Basis Affirmed Reversed
1–3, 5–13,
15–22
101 Eligibility 1–3, 5–13,
15–22

No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a)(1)(iv).
AFFIRMED